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Electronic Theses and Dissertations Theses, Dissertations, and Major Papers

2011

Effects of tryptophan manipulation on neuropsychological performance

Kristen Kaploun University of Windsor

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Effects of Tryptophan Manipulation on Neuropsychological Performance

by

Kristen A. Kaploun

A Dissertation Submitted to the Faculty of Graduate Studies through the Department of Psychology in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy at the University of Windsor

Windsor, Ontario, Canada 2010 © 2010 Kristen A. Kaploun Effects of Tryptophan Manipulation on Neuropsychological Performance iii

Author’s Declaration of Originality

I hereby certify that I am the sole author of this dissertation and that no part of this dissertation has been published or submitted for publication.

I certify that, to the best of my knowledge, my dissertation does not infringe upon anyone’s copyright nor violate any proprietary rights and that any ideas, techniques, quotations, or any other material from the work of other people included in my dissertation, published or otherwise, are fully acknowledged in accordance with the standard referencing practices. Furthermore, to the extent that I have included copyrighted material that surpasses the bounds of fair dealing within the meaning of the Canada Copyright Act, I certify that I have obtained a written permission from the copyright owner(s) to include such material(s) in my dissertation and have included copies of such copyright clearances to my appendix.

I declare that this is a true copy of my dissertation, including any final revisions, as approved by my dissertation committee and the Graduate Studies office, and that this dissertation has not been submitted for a higher degree to any other University or Institution. Effects of Tryptophan Manipulation on Neuropsychological Performance iv

Abstract

The purpose of this study was to examine the effects of tryptophan, the amino

acid precursor to serotonin, on neuropsychological performance. A dietary method of tryptophan manipulation was employed to temporarily raise, lower, or maintain circulating levels of tryptophan within the body, allowing the resulting cognitive and affective sequelae to be measured. A total of 73 participants (50 females, 23 males) completed this mixed-design, double-blind study. Participants were quasi-randomly assigned to one of three tryptophan conditions (augmented, depleted or balanced) and were provided with breakfast, lunch and a snack. A comprehensive neuropsychological test battery was administered 1.5 hours after completion of lunch. Analyses were conducted on each gender separately. No significant results were found for females. For the males, however, significant between-group differences were found for the Rey-O delayed recall, with those in the Depletion group scoring significantly higher than those in the Balanced or Augmented conditions. Males in the Augmented condition also performed better than those in the Balanced or Depleted condition on the speed component of the Ruff 2 & 7 Selective Attention Test. With regards to affect, males in the Augmented group demonstrated a near-significant difference on the PANAS positive affect scale on the fourth PANAS administration compared to those in the Depleted group. These differences in positive affect levels seem to be primarily driven by the trend in excitement levels between males in the Augmented and Depleted conditions over time. Results of this study support the hypothesis that dietary manipulations aimed at Effects of Tryptophan Manipulation on Neuropsychological Performance v altering tryptophan levels had an effect on some cognitive tests and positive affect, at

least with regards to males.

Effects of Tryptophan Manipulation on Neuropsychological Performance vi

Acknowledgments

First and foremost, I would like to thank my advisor, Dr. Chris Abeare, for all his support and guidance during the formulation and completion of this project in particular, and through my entire graduate school career, in general. Despite my research interests dragging him into areas beyond his ken, he was always willing to let me forge ahead (at times perhaps against his better judgement) and to help me when I floundered. Through his guidance, Dr. Abeare has allowed me to discover my own potential as a researcher and indeed as a scientist-practitioner.

I would also like to thank my committee members, Dr. Julie Hakim- Larson, Dr. Alan Scoboria, and Dr. Nancy McNevin for their thoughtful critiques and helpful insights. Their feedback enabled me to turn a fanciful idea into a well-thought out reality, resulting in a much stronger project. I thank them for their time, commitment and genuine interest in my research topic.

I am also indebted to my lab mate, Olivia Chu, and to my colleagues, Shelley Ylioja and Aleks Milosevic, who were willing to listen and offer suggestions when I found myself at an impasse. Their interest, support and encouragement helped me maintain momentum and stay on track to accomplish this lofty project in little over one year.

Special thanks is also owed to my research assistant, the wonderfully motivated, energetic, dedicated and ceaselessly optimistic Sabrina Freund, who never faltered or complained when asked to come into the lab every day of the week (including weekends) to run participants. This project could not have been completed had it not been for Sabrina’s assistance, organizational skills and ability to keep me in line when things got too unruly. Her endless enthusiasm and easy smile reminded me that no matter how hard the work is, you can still have fun while doing it. Thanks is also due to my other research assistants, Sam Iskander and Bojana Knezevic, both of whom were able to come in when needed to run extra participants.

On a personal note, I would like to thank my husband, Maxim Kaploun, for all his patience, support and understanding throughout the duration of this study and my entire graduate school career. His ability to make me laugh when I needed it most helped me keep things in perspective and reminded me not to take myself too seriously. I am also indebted to his ability to listen to endless repetition of the same three movies during all stages of the writing process. I would also like to thank my parents, Bill and Renie Hodges, my brother and sister-in-law, Paul and Jen Hodges, my husband’s family, Ilya, Luba and Hanna, and my best friend Carley Severnuk and our close friend Tatha Swann for their endless encouragement and wonder. Their interest and support has allowed me to accomplish goals of which I had never dreamt for myself. Effects of Tryptophan Manipulation on Neuropsychological Performance vii

Lastly, I would like to thank all the students who volunteered their time to take part in this very involving study. Without their willingness to participate, this would be a pretty short dissertation.

Funding for this project was provided by Natural Sciences and Engineering Research Council of Canada.

“If we knew what it was we were doing, it would not be called research, would it?”

- Albert Einstein viii

TABLE OF CONTENTS

AUTHOR’S DECLARATION OF ORIGINALITY iii ABSTRACT iv ACKNOWLEDGEMENTS vi LIST OF TABLES xi LIST OF FIGURES xiii

I. INTRODUCTION 1

Neurochemistry Review 2

The Amino Acids 2

The Blood-brain Barrier 4

Tryptophan:LNAA Ratios 5

Serotonin Synthesis 8

Serotonin Innervation and Functional Neuroanatomy 12

Serotonin, Mood and Cognitive Performance 22

Relationship Between Serotonin, Depression, and

Antidepressants 25

Effects of Other Tryptophan Metabolites on Brain Function 27

Effects of Tryptophan Augmentation or Depletion on 30

Neuropsychological Performance

Amino Acid Protocol 30

Dietary Manipulations 40

Purpose and Hypotheses of the Present Study 50

II. METHOD 52

Participants 52

Design 54 ix

Procedure 54

Screening Session 54

Testing Session 62

Dietary Manipulations 65

Neuropsychological Tests Administered 67

Executive Functions 67

Verbal Fluency (FAS + Animals) 67

Stroop Color-Word Test 68

Emotional Stroop 69

Attention/Concentration 70

Digit Span 70

Letter-Number Sequencing 71

Digit Symbol – Coding 72

Ruff 2 & 7 Selective Attention Test 72

Trail Making Test 73

Memory 74

California Verbal Learning Test – II 74

Rey-Osterrieth Complex Figure Test 75

Mood/Affect 75

Positive and Negative Affect Scales 75

Beck Depression Inventory – II 76

III. RESULTS 77

Exploratory Analyses 104 x

IV. DISCUSSION 112

Did the Manipulation Affect Affect? 114

Did the Manipulation Affect Cognitive Functioning? 125

Strengths of the Current Study 133

Limitations of the Current Study 137

Is Dietary Manipulation An Effective Means of Measuring

Tryptophan Manipulation? 141

Summary and Future Directions 144

REFERENCES 149

APPENDIX A Glossary of Terms 180

APPENDIX B Study Advertisement (Participant Pool) 182

APPENDIX C Screener 183

APPENDIX D Study Advertisement (Community Sample) 188

APPENDIX E Screener Consent Form 189

APPENDIX F Testing Session Consent Form 193

APPENDIX G Composition of Tryptophan Augmented (ATA),

Tryptophan Depleted (ATD), and Balanced (B)

Meals And Snacks 197

VITA AUCTORIS 199

Effects of Tryptophan Manipulation on Neuropsychological Performance xi

LIST OF TABLES

Table 1 Summary of Findings in the Literature 47

Table 2 Demographic Information for Each Condition 55

Table 3 Schedule of Events 64

Table 4 Macronutrient Content of Each Condition 66

Table 5 Correlations Between Background Variables and Tests

Comprising Predictions and Composite Scores 78

Table 6 Chi-square Results for Proportion and Percent Total

of Dichotomized Physical Activity Levels by Meal

Type for Females 83

Table 7 Chi-square Results for Proportion and Percent Total

of Dichotomized Physical Activity Levels by Meal

Type for Males 84

Table 8 Mean and Standard Deviation of BMI Scores by Gender

and Meal type 86

Table 9 Mean and Standard Deviation of Test Scores on Digit

Span Backward 2 Scores by Gender and Meal Type 88

Table 10 Mean and Standard Deviation of Test Scores on Negative

Affect (NA) Scale Scores by Gender and Meal type 90

Table 11 Mean and Standard Deviation of Test Scores on Positive

Affect (PA) Scale Scores by Gender and Meal type 93

Effects of Tryptophan Manipulation on Neuropsychological Performance xii

Table 12 Mean and Standard Deviation of Test Scores on the CVLT

Long Delay Free Recall and the Rey-O Long Delay

by Gender and Meal type 96

Table 13 Mean and Standard Deviation of Test Scores on the Negative

and Positive EStroop by Gender and Meal type 98

Table 14 Mean and Standard Deviation of Test Scores on the Working

Memory Composite by Gender and Meal Type 100

Table 15 Mean and Standard Deviation of Test Scores on the Attention

Composite by Gender and Meal type 102

Table 16 MANOVA for Each PANAS item for Females 106

Table 17 MANOVA for Each PANAS item for Males 107

Table 18 Mean and Standard Deviation of Excited Item Over Time

for Males 109

Table 19 ANOVAs on the Effect of Meal Type on All Test Measures

Examined in Exploratory Analyses, Separated by

Gender 113 Effects of Tryptophan Manipulation on Neuropsychological Performance xiii

LIST OF FIGURES

Figure 1 Flow chart depicting the enzymes responsible for converting 10

tryptophan into serotonin (5-HT).

Figure 2 Mean Excited scores by meal type over time. 111 Tryptophan 1

Effects of tryptophan manipulation on neuropsychological performance

Human behaviour is continuously influenced by factors stemming from the

external environment and from internal systems. The reaction to these stimuli is

mediated by the central nervous system (CNS), in part through chemical messengers

known as neurotransmitters (see Appendix A for glossary of terms). Of all the

neurotransmitters in the mammalian CNS, serotonin, one of the main metabolic products

of tryptophan, has received a great deal of interest within the literature. In particular, the

focus of most research studies on serotonin has been on the association between the neurotransmitter and mood (Benkelfat, Ellenbogen, Dean, Palmour, & Young, 1994;

Flory, Manuck, Matthews & Muldoon, 2004; Heninger, Delgado, Charney, Price &

Aghajanian, 1992; Smith, Pihl, Young, & Ervin, 1987; S. N. Young, Smith, Pihl, &

Ervin, 1985). However, a growing body of evidence suggests that serotonin also plays a

role in many cognitive functions (e.g., Lieberman, 2003). Given that serotonin and it’s precursor (tryptophan) are derived from foods that are consumed (Sirek & Sirek, 1970), there is growing support for the notion that diet can produce reliable effects on tryptophan levels and thus, on cognitive performance (e.g., Dye, Lluch & Blundell,

2000), presumably through the serotonergic pathway (one of the major pathways resulting from tryptophan metabolism). In order to examine this notion, the neurochemistry behind tryptophan entering the body and becoming converted to serotonin will first be reviewed. Following this review, the role of serotonin innervation, function, and the neuroanatomical structures related to the serotonergic system, as well as those related to the other pathways of tryptophan metabolism, will be discussed. Finally, Tryptophan 2

this paper will examine the methods by which tryptophan levels can be manipulated.

This study will investigate the effects of tryptophan on neuropsychological performance.

Neurochemistry Review

In order to fully understand the ways in which tryptophan can exert its influence on cognitive and affective responses to stimuli in the environment, it is first necessary to

understand the neurochemical bases of serotonin synthesis via tryptophan metabolism.

The entire process begins with the ingestion of nutrients that are metabolized in order to

provide the necessary amino acids for neurotransmitter synthesis to occur. Thus, the first

step in this process begins with the amino acids.

The Amino Acids

Three of the main components in the mammalian central nervous system (CNS) –

peptides, amines, and non-essential amino acids (Wurtman, Hefti & Melamed, 1981) –

are heavily dependent upon the ingestion and/or creation of amino acids. Amino acids

are critical to proper nutrition and are the building blocks of both proteins and peptides.

Although proteins are essential macronutrients responsible for the growth and

development of the body, including bones, skin, muscle and blood, as well as for the

repair of tissues (Blass, 1994), it is the peptides that are a major component of the

mammalian CNS. Peptides are the chemical messengers of the CNS and are broadly

distributed throughout the nervous system (Brownstein, 1994).

When amino acids are broken down, amines are the resulting product. Amines,

which comprise the second main component of the CNS, are involved in the production

of neurotransmitters. Based on their structure, amines are the building blocks of either Tryptophan 3

the catecholamines (e.g., epinephrine, norepinephrine, or dopamine) or the indolamine

serotonin (Pinel, 2006). Serotonin in an example of a monoamine, meaning it is

synthesized from a single amino acid. Compared to amino acids, monoamines are a group of small-molecule neurotransmitters that are produced by cell bodies that are mainly located in the brain stem (Pinel, 2006). Neurotransmitters are released more diffusely from monoamines than from amino acids as their axons are highly branched with many varicosities (i.e., swellings along the axon of the presynaptic neuron that release neurotransmitters), enabling more widespread release of neurotransmitters into the extracellular space (Bunin & Wightman, 1999) serving a neuromodulatory function.

The third main component of the mammalian CNS is that of the non-essential amino acids. There are twenty standard amino acids, of which twelve are classified as non-essential; the remaining eight are comprised of essential amino acids. The title of

“essential” versus “non-essential” relates not to the importance of a given amino acid, as all are crucial for optimal health, but rather it relates to the means by which the body obtains the amino acids. Non-essential amino acids, such as glutamine, can be synthesized by the human body from essential amino acids or via the catabolism of proteins. Essential amino acids such as tryptophan, however, cannot be produced by the body and thus they must be obtained through the ingestion of food (Wurtman, et al.,

1981). The distinction between the eight essential amino acids (isoleucine, leucine, lysine, methionine, phenylalanine, threonin, tryptophan, and valine) (V. R. Young, 1994) and the three semi-essential amino acids (histidine, tyrosine, and arginine) is that the

latter can be synthesized by the adult human body but not by infants and growing

children whose metabolic pathways are in the process of development (V. R. Young, Tryptophan 4

1994). Both essential and non-essential amino acids are the major constituents involved

in the creation of proteins (Barondes, 1974; Blass, 1994).

Although not strictly one of the three essential components of the mammalian

CNS, essential amino acids play a major role in neurotransmitter synthesis. Based upon

their chemical composition, essential amino acids can be classified into the aromatic

amino acids (tryptophan, tyrosine, phenylalanine and histidine), the branched-chain

amino acids (leucine, isoleucine, and valine), and the other amino acids (threonine and

methionine) (Cooper, Bloom & Roth, 1996; Paul & Southgate, 1978; Wurtman et al.,

1981). All three groups are examples of ‘large neutral amino acids’ (LNAAs), a term

used to describe amino acids that compete with each other for uptake into the brain and

subsequent neurotransmitter synthesis (Curzon, 1985; Wurtman et al., 2003). Brain

levels of neurotransmitters will change depending on the levels of the precursor(s) in the

blood plasma, as will changes in blood plasma levels of competing LNAAs (Fernstrom &

Wurtman, 1972). Ultimately, however, it is the transport systems of the blood-brain

barrier that determine which transmitters will gain access to the brain.

The Blood-brain Barrier

The blood-brain barrier is comprised of capillary endothelia with tight junctions

between cells that create a continuous membrane separating the brain from circulating

blood and preventing many harmful or toxic substances from gaining access to the brain

(Betz, Goldstein & Katzman, 1994; Brightman, Reese & Feder, 1970; Oldendorf, 1976;

Pinel, 2006). According to Oldendorf, there are two ways in which molecules can cross

the blood-brain barrier: 1) lipid-mediation, through which lipid-soluble molecules can

easily pass; and 2) carrier-transport systems, in which special transport carriers are Tryptophan 5 needed to carry the molecules through the blood-brain barrier. As LNAAs are not lipid- soluble (Betz et al., 1994), Pardridge and others (Pardridge & Oldendorf, 1977;

Wurtman, et al., 2003) posit that there is a special transport system for LNAAs that enables them to cross the blood-brain barrier. As many of the LNAAs serve as neurotransmitter precursors, they must compete with each other for access to the carrier molecules (Pardridge & Oldendorf, 1977). Thus, those LNAAs with the highest blood plasma concentrations are most likely to gain access to the carrier molecules, enabling them to cross the blood-brain barrier and thus to alter the levels of brain neurotransmitters

(Cooper et al., 1996). Essential amino acids that serve as precursors to catecholamines or indolamine are readily admitted via the leucine-preferring system (L-system), whereas the alanine-system (A-system) serves to limit entry of the non-essential amino acids and actively transports them out of the brain (Betz et al., 1994; Oldendorf, 1971). In other words, the essential amino acids are rapidly and broadly swept into the brain from the blood, whereas the non-essential amino acids are not as readily exchanged (Oldendorf,

1971). It is for this reason that Pardridge and Oldendorf (1977) state that “… the blood- brain barrier amino acid transport probably is the limiting factor in determining availability of amino acids in the brain” (p. 8). Thus, even though the essential amino acids can cross the blood-brain barrier with greater ease, they must compete for access to the carrier systems. It is this function, in addition to the ratio of each amino acid, which serves to limit the synthesis of neurotransmitters.

Tryptophan:LNAA Ratios

An additional factor that influences the rate of amino acids crossing the blood- brain barrier is the ratio of each amino acid and whether or not there is competition with Tryptophan 6

other molecules for carrier transport. For example, tryptophan is the least abundant of the amino acids (Paul & Southgate, 1978; Wurtman, 1970; Wurtman & Fernstrom, 1972;

Wurtman et al., 1981). As mentioned previously, the LNAAs (which include tryptophan) compete with each other for access to the blood-brain barrier transport molecules. Thus, the other LNAAs gain access to transport carriers and cross the blood-brain barrier in greater volumes than tryptophan simply because they are more abundant. The reasons for the greater abundance of the other LNAAs as compared to tryptophan are at least three- fold. First, although the main source of tryptophan is from dietary protein (Munro, 1974), tryptophan comprises only a fraction of the total amino acid content of most dietary protein (approximately 1 to 1.6% compared to 25% for the LNAAs) (Wurtman, 1970).

For this reason, the ingestion of protein greatly increases levels of the LNAAs, thereby maintaining the lowered tryptophan:LNAA ratio. Second, half of all tryptophan that is ingested is excreted in the urine without being converted into serotonin (Sirek & Sirek,

1970). Finally, tryptophan is the only LNAA that is metabolized by the liver into kynurenine, which in turn is used in the synthesis of niacin; a key function of niacin is the metabolism of carbohydrates. Since enzymes found in the liver can also break tryptophan into smaller proteins, the actions of the liver result in less tryptophan being available for systemic circulation (Brown, 1980).

Thus, it is clear that there are many factors at work to maintain the tryptophan:LNAA ratio. According to Fernstrom and Faller (1978), “… competition among tryptophan and other large neutral amino acids in blood is a very important, and perhaps dominant, determinant of tryptophan uptake into the brain” (p. 1537). There are, however, two ways in which the ratio of tryptophan to LNAAs can be altered, which in Tryptophan 7

turn will alter the rate of transport of the different amino acids across the blood-brain

barrier. The first method of raising plasma tryptophan levels is by ingesting greater quantities of tryptophan-containing foods or supplements. Although this might seem like a good technique in principle, it is in fact a poor method of altering the tryptophan levels.

This is because ingesting dietary protein, albeit the main source of tryptophan, also raises the levels of LNAAs competing for transport across the blood-brain barrier. For example, consuming a meal that contains 10% protein will raise tryptophan in levels that are proportionate to the raise in LNAAs (Fernstrom & Faller, 1978; Fernstrom &

Wurtman, 1972). Thus, brain tryptophan levels will actually decrease due to increased competition from the other LNAAs that utilize the same transport carrier (Blass, 1994).

According to Teff, Young, and Blundell (1989), even 4% protein in an otherwise protein- free meal will prevent a rise in tryptophan levels compared to that of the LNAAs, while an amino acid mixture (100 g) that does not contain tryptophan will effectively reduce tryptophan plasma levels by 70 to 90% (S. N. Young, Ervin, Pihl & Finn, 1989). Thus, it is clear that simply raising tryptophan levels will not suffice in adequately altering the tryptophan:LNAA ratio.

The alternative method, which appears to be the most rapid and most effective means of altering the tryptophan:LNAA ratio, is by lowering levels of the other LNAAs through the ingestion of carbohydrates (i.e., “carb-loading”). The consumption of carbohydrates results in an increase in insulin levels, which in turn lowers plasma levels of the LNAAs by drawing them into the surrounding tissue (Wurtman et al., 1981).

Tryptophan, however, is impervious to this effect, presumably because approximately 70 to 80% of plasma tryptophan is albumin-bound which prevents its penetration into Tryptophan 8

peripheral cells (Blum et al., 1992; Lyons & Truswell, 1988; McMenamy, Lund &

Oncley, 1957). Thus, ingesting carbohydrates essentially clears the way for tryptophan to

travel to the blood-brain barrier and gain priority access to the carrier transport molecules

which deliver it into the brain where it can be synthesized into serotonin.

Serotonin Synthesis

All neurotransmitters are synthesized from precursors that are stored as tissue

proteins until needed. The essential amino acid tryptophan serves as the precursor for the

indolamine serotonin (5-hydroxytryptamine, 5-HT), a neurotransmitter found throughout

the brain and body. Originally discovered due to its effects on smooth muscle

contraction, serotonin was simultaneously yet independently discovered by Ersparmer

(1940) in Italy and by Rapport, Green and Page (1948) in Cleveland, USA. Both groups noticed that following blood clotting a substance was found within the serum that appeared to cause vasoconstriction. The “tonic” effect of the serum substance was eventually termed “serotonin” and was subsequently found to have a wide array of effects on the body (Sirek & Sirek, 1970).

As shown in Figure 1, serotonin is created via a three-step process, starting with the precursor tryptophan. Through the utilization of a single oxygen atom, the rate- limiting enzyme tryptophan hydroxylase (which is only found in cells that produce 5-HT) converts tryptophan into 5-hydroxytryptophan (5-HTP) (Frazer & Hensler, 1994; Sirek &

Sirek, 1970). Serotonin is almost immediately synthesized once tryptophan is converted to 5-HTP (Cooper et al., 1996) through the action of the aromatic amino acid decarboxylase, an enzyme that removes a carboxyl group (Sirek & Sirek, 1970). The resultant 5-HT is eventually degraded by monoamine oxidase through the removal of an Tryptophan 9

amine group (Sirek & Sirek, 1970). The main product generated through the catabolism

of 5-HT is 5-hydroxyindole acetic acid (5-HIAA), which is excreted through the urine

(Frazer & Hensler, 1994). It is estimated that the average human expels between 1 and

10 mg of 5-HIAA per day (Sirek & Sirek, 1970). As aromatic amino acid decarboxylase is not normally saturated in the human brain, levels of 5-HT can thus be boosted either through increasing 5-HTP itself (e.g., via supplementation), or by increasing tryptophan

(e.g., via the ingestion of carbohydrates) which will in turn increase levels of 5-HTP, and thus of 5-HT (Frazer & Hensler, 1994). Furthermore, although 5-HTP is only found in trace amounts in the brain (Frazer & Hensler, 1994), it is lipid-soluble (unlike tryptophan), and is therefore able to cross the blood-brain barrier without a carrier transport. In this way, 5-HTP can act directly to increase brain serotonin levels (Murray,

1998). It is important to note, however, that of the approximate 10 mg of 5-HT found in an adult male (Sirek & Sirek, 1970), only about 1-2% of that total amount is found in the brain. Within the brain, however, the pineal gland acts as the factory for producing 5-HT as it contains the enzymes necessary to convert tryptophan into 5-HT (Frazer & Hensler,

1994). The metabolic activity of the pineal gland, which is located outside of the blood- brain barrier, is directly influenced by external factors such as light from the environment

(via sympathetic innervation) that regulate the daily rhythmic cycle of 5-HT synthesis

(Cooper et al., 1996).

Tryptophan 10

Figure 1. Flow chart depicting the enzymes responsible for converting tryptophan into serotonin (5-HT).

5-Hydroxyindole Tryptophan Acetic Acid (5-HIAA)

+ tryptophan hydroxylase

5-Hydroxytryptophan (5-HTP)

+ 5-hydroxytryptophan decarboxylase

5-Hydroxytryptamine (5-HT)

+ monoamine oxidase (MAO)

5-Hydroxyindole Acetic Acid (5-HIAA) Tryptophan 11

In order for tryptophan, 5-HTP, or any other precursor to successfully change the

rate of neurotransmitter synthesis, however, five conditions must be met: 1) food consumption must produce equivalent increases in the amount of neurotransmitter precursors in the plasma levels; in other words, there must be no mechanism working to keep plasma levels within a strictly controlled and constant range; 2) a mechanism must be in place to enable the precursor access to the brain via the blood-brain barrier; 3) raising plasma levels of the precursor must be able to further saturate transport carriers so as to increase the amount of a given precursor gaining access to the brain (i.e., transport carriers must maintain a sub-threshold level of saturation); 4) there must be a low affinity between the enzyme and the precursor, resulting in poor binding and inefficient catalysis; the precursor will act as the rate-limiting factor in the genesis of the neurotransmitter; and

5) the enzyme must be free of significant inhibitory feedback from the creation of its product (i.e., it must not “turn itself off” after producing a specific amount of its neurotransmitter) (Wurtman et al., 1981). With regards to these conditions, Carlsson and

Lindqvist (1978) have found that the enzyme tryptophan hydroxylase is only 50 to 75% saturated with tryptophan, indicating that the enzyme is not normally saturated in the mammalian brain (Cooper et al., 1996; Curzon & Knott, 1974; Frazer & Hensler, 1994;

Gessa & Tagliamonte, 1974; S. N. Young, 1993). Further, Lovenberg, Jequier, and

Sjoerdsma (1968) posit that there is no evidence to suggest that 5-HT inhibits tryptophan hydroxylase, thereby decreasing its own rate of production. Of note, Gallager and

Aghajanian (1976) did find evidence that the rate of firing of 5-HT neurons in the raphe nuclei slows after the administration of large doses of tryptophan, resulting in decreased release, and perhaps decreased generation, of 5-HT. However, since such instances do Tryptophan 12 not normally occur without external manipulation, it appears that there is minimal feedback control of 5-HT synthesis under normal conditions. Thus, according to Spring

(1986), tryptophan meets all five conditions for ensuring successful alteration of the rate of serotonin synthesis.

Up until this point, we have discussed the process of metabolism by which the amino acid tryptophan gets converted into serotonin, the indolamine neurotransmitter involved in many different functions throughout the brain and body. This next section will detail the routes of serotonin innervation within the brain and will discuss the specific neuroanatomical structures innervated by these pathways that are implicated in various cognitive functions. There is, however, a gap in this literature that cannot fully be bridged as not enough is currently known about the effects of tryptophan manipulation on neuroanatomical function. A better understanding of these pathways would enable more precise and accurate predictions about the role of tryptophan on specific neuroanatomical structures and functions.

Serotonin Innervation and Functional Neuroanatomy

Serotonergic neurons have diffuse branching axons innervating much of the CNS

(Frazer & Hensler, 1994; Tork, 1990). The majority of their somas can be found along the brainstem midline, especially in the raphe nuclei of the brainstem, the pons and medulla (Cooper et al., 1996; Frazer & Hensler, 1994). These latter nuclei act as

“variable ratio sensors” (Wurtman et al., 1981, p. 323) by keeping the rest of the brain informed about the body’s metabolic status. This information is in turn used to help determine which actions should be carried out next (e.g., deciding which foods should be consumed at the next meal). In more general terms, serotonin receptors are located Tryptophan 13

throughout the brain and spinal cord (e.g., the amygdala, hippocampus, hypothalamus,

and substantia nigra, as well as all layers of the cerebral cortices) (Graeff, 1997; Molliver,

1987; Palacios, Waebar, Hoyer & Mengod, 1990), with each area being responsive to

certain types of input and nonresponsive to others. Forebrain regions in control of

physiological functions are the termination points for ascending projections, while the

spinal cord is the end terminal for descending projections (Tork, 1990). Until its release

into the synapse via exocytotic mechanisms (Sanders-Bush & Martin, 1982), vesicles in

the terminal buttons of the pre-synaptic neuron store the serotonin molecules. The rate of

release is determined by the rate of firing of serotonergic cells (Frazer & Hensler, 1994).

Once released, the activity of 5-HT is terminated via reuptake at the serotonergic

terminals. Generally speaking, the serotonergic pathways emerge from the dorsal and the

medial raphe nuclei and project to various neuroanatomical structures (Takagi, Shiosaka,

Tohyama, Semba & Sakanaka, 1980). The routes of serotonergic innervation throughout

the brain, however, are extensive, influencing several different and, in many cases,

overlapping neuroanatomical structures and functions. The specific contributions of

these structures to cognitive functioning are the focus of this next section.

Memory and Learning. Many different regions of the brain are involved in

different types of memory. The most well-known of these structures is the hippocampus,

a pair of seahorse-shaped structures that line the inner fold of each side of the temporal

lobes (Lezak, Howieson & Loring, 2004). The ventral hippocampus receives serotonergic innervation from dorsal raphe projections, whereas the dorsal hippocampus receives serotonergic innervation from the medial raphe nuclei (Graeff, 1997; Molliver,

1987; Steckler & Sahgal, 1995). The hippocampus plays a major role in normal learning Tryptophan 14

and retention, quickly associating and integrating information from multiple cortical

areas (Eichenbaum & Cohen, 2001). Serving as an index of where each memory is

stored in the neocortex (Schacter, Norman, & Koutstaal, 1998), the hippocampus encodes

information about events and the context in which they occurred, as well as the thoughts

and emotions that were triggered by them. These multiple pieces of information (i.e.,

“new” memories) are then consolidated and stored in the neocortex as “older” memories

(Fuster, 1995). The hippocampus plays a particular role in spatial memory as the perceptual and memory systems are closely linked (Zola & Squire, 2000).

The dorsomedial nucleus of the thalamus is also implicated in memory. It has significant reciprocal pathways to the prefrontal cortex (Graff-Radford, 2003), as well as

receptive pathways with the amygdala, temporal cortex, hypothalamus and interthalamic

nuclei (Afifi & Bergman, 1998). The dorsomedial nucleus of the thalamus receives

serotonergic innervation via dorsal raphe projections (Cooper et al., 1996; Steckler &

Sahgal, 1995). Damage to these projections or to the dorsomedial thalamic nucleus

would presumably result in decreased availability of serotonin which would result in

functional impairments in memory.

The neostriatum, part of the basal ganglia, is also involved in memory. More

specifically, it is involved in procedural memory (Fuster, 1995), and it also plays a role in

devising novel solutions to new situations (Saint-Cyr & Taylor, 1992). The neostriatum

and the basal ganglia both receive serotonergic innervation via dorsal raphe projections

(Cooper et al., 1996; Graeff, 1997; Steckler & Sahgal, 1995).

Several components of the limbic system, which is comprised of numerous

structures including the amygdala, the cingulate gyrus, and the hippocampus Tryptophan 15

(Markowitsch, 2000), are also involved in learning and memory. The limbic system,

which is spread through the brain stem (e.g., reticular activation system) and the cortex

(e.g., olfactory bulb of the frontal cortex) (Lezak et al., 2004), are involved in memory, emotions, and motivation (Damasio, 1994; Markowitsch, 2000). The limbic system receives serotonergic innervation from both dorsal and medial raphe projections (Cooper et al., 1996; Graeff, 1997; Steckler & Sahgal, 1995). The mammillary bodies and the fornix, two other limbic components which are located within the posterior part of the hypothalamus, aid in the retention and consolidation of memories. The fornix connects the hippocampal areas of the forebrain with those of the mammillothalamic regions of the limbic system (Markowitsch, 2000); damage to the mammillary bodies impairs memory processing (Tanaka, Miyazawa, Akaoka & Yamanda, 1997). The amygdala, a small almond-shaped structure found deep in the anterior portion of the temporal lobe, is also involved in memory formation and consolidation by way of object recognition (Mishkin

& Appenzeller, 1987) and by providing an emotional component to memories (Doty,

1990). It has extensive connections with many areas of the brain, including the nuclei in the brain stem, cerebral cortex, hypothalamus, thalamus, hippocampus, and basal ganglia

(Lezak et al., 2004).

Lastly, the cerebellum, which is attached to the brainstem at the base of the brain, plays a role in memory and learning through its non-motor connections to the thalamus and via input received from the frontal, partietal and superior temporal cortices

(Schmahmann & Sherman, 1998). In this way, the cerebellum influences learning and memory in general (Nyberg, 1998), as well as working memory (Desmond, Gabrieli,

Wagner, Ginier, & Glover, 1997). Temporal, parietal, frontal and cerebellar cortices, as Tryptophan 16 well as all layers of the cerebral cortex, receive the majority of their serotonergic innervation from the dorsal raphe nuclei (Graeff, 1997; Molliver, 1987).

Overall, the literature on serotonergic influences on memory are inconsistent as

Riedel, Eikmans, Heldens and Schmitt (2005) found that citalopram, a selective serotonin reuptake inhibitor (SSRI), results in impairments in delayed memory recall, whereas others have found that increased levels of serotonin improved memory and learning (e.g.,

Luciana, Burgund, Berman & Hanson, 2001; Park et al., 1994).

Attention. As with memory, many different neuroanatomical structures are employed in the process of arousal and attending to stimuli. The reticular formation is a network of reciprocal nerve fibers connecting the lowest part of the brainstem (the medulla oblongata) to all major cortical tracts. The reticular formation contains the reticular activating system which is involved in attention through its arousal of the cerebral cortex (Mesulam, 2000). The reticular activating system is responsible for alertness and for maintaining wakefulness (Mirsky, 1989). Lesions to this system result in disturbances in sleep and general responsivity (Lezak et al., 2004). Serotonergic innervation is mainly received from dorsal raphe projections (Steckler & Sahgal, 1995).

The thalamus also plays a role in attention (Corbetta, Miezin, Dobmeyer,

Shulman & Petersen, 1991) by way of its connections with the reticular activating system

(Steriade, Jones & Llinas, 1990). The thalamus, a pair of small, oval-shaped structures lying along both sides of the third ventricle within the forebrain and above the hypothalamus, is known as the “relay station” of the limbic system and of the brain as a whole as it is involved in many different functions and has extensive reciprocal and topographically organized cortical connections, including pathways to the premotor, Tryptophan 17

prefrontal, temporal and parietal cortices (Kolb & Whishaw, 1996; Sherman & Koch,

1998). The role of the thalamus in attention is illustrated by reductions in awareness to

stimuli on the side opposite the damaged thalamus (Heilman, Watson, & Valenstein,

2003). As with the dorsomedial nucleus, the thalamus receives serotonergic innervation

via dorsal raphe projections (Cooper et al., 1996; Steckler & Sahgal, 1995).

Components of the limbic system also play a role in attention. The ability to

attend to stimuli is influenced by the amygdala (Eichenbaum & Cohen, 2001), but also by

the cingulate cortex, a structure located deep within the brain above the corpus callosum.

The amygdala has projections that terminate in the anterior portion of the cingulate cortex, influencing attention (Chelazzi & Corbetta, 2000), whereas the posterior portion is, in part, innervated by the hippocampus, thereby also implicating it in memory functions (Mesulam, 2000). Serotonergic innervation to the amygdala is via dorsal raphe projections (Steckler & Sahgal, 1995), whereas the cingulate cortex receives its innervation from medial raphe projections.

The cerebellum is also known to play a role in attention (Middleton & Strick,

2000a), and lesions to the white matter of the intercerebral conduction pathways that link the two hemispheres results in impairments in attention (Filley, 2001). As mentioned previously, the cerebellum is innervated by dorsal raphe projections (Cooper et al., 1996), whereas both the dorsal and the medial raphe projections are likely involved in innervating the white matter (Cooper et al., 1996; Graeff, 1997; Steckler & Sahgal,

1995).

Taken together, increasing serotonin would be expected to improve attention

(Lieberman, Falco & Slade, 2002) through an effect on the reticular activation system, Tryptophan 18

resulting in increased arousal and vigilance. However, greater levels of serotonin may

also impede certain aspects of attention (e.g. auditory and visual attention; Schmitt et al.,

2000) and vigilance (Riedel et al., 2005) presumably by way of an inhibitory effect on the amygdala, the thalamic nuclei or cerebellar structures.

Executive Functioning. The term ‘executive functioning’ is a catch-all phrase pertaining to most higher-level cognitive functions, including such diverse functions as

planning, cognitive flexibility, and abstract reasoning, among others. Thus, it is not

surprising that, as with memory and attention, many different neuroanatomical structures

are involved in these diverse functions. For example, several researchers have found that

the cerebellum, though primarily thought of for its motor control, plays a role in abstract

reasoning (Middleton & Strick, 2000a), planning (Dow, 1998), set-shifting (Le, Pardo, &

Hu, 1998), and information processing speed (Botez, Gravel, Attig, & Vezina, 1985), as

well as in more language-based functions such as linguistic processing (Leiner, Leiner, &

Dow, 1989), and word generation (Raichle, 2000). It does this through its non-motor

pathways. Lesions to these pathways would presumably decrease the amount of

serotonin available to the structures innervated by these cerebellar pathways and,

although it has been found that information processing slows as a result (e.g., Botez et al.,

1985), it is unclear whether any effects on these cognitive processes result from decreases

in brain tryptophan (and thus, presumably, serotonin) (e.g., Fischer, Colombani,

Langhans & Wenk, 2002; Hughes et al., 2003; Luciana et al., 2001; Rogers et al., 1999;

Schmitt et al., 2000).

Each of the three main areas of the frontal cortex (premotor, motor and prefrontal

cortices) is differentially innervated, albeit with some overlap. The premotor cortex, Tryptophan 19

which is responsible for selecting a movement, receives input from the prefrontal cortex

and parietal areas, whereas the motor cortex, which is responsible for carrying out a

movement, projects to the basal ganglia and red nucleus (involved in motor

coordination). The prefrontal cortex, which receives its input from the parietal and

temporal lobes, projects to the cingulate cortex, the basal ganglia, the amygdala and the

hypothalamus (Kolb & Whishaw, 1996); this area is involved in the control of executive

functions. The frontal cortex is innervated by both medial and dorsal raphe projections

(Graeff, 1997). On a simplistic level, the frontal cortex is considered the primary

location of executive functioning, although it is known that input into these functions are

provided by most neuroanatomical structures in the brain (Lezak et al., 2004). Lesions to

the frontal lobes tend to produce deficits in “reciprocal relationships between the major

functional system” (Lezak et al., 2004, p. 78). This includes the limbic, sensory, motor

and executive systems, resulting in deficits of integrating such varied constructs as

memory, attention, drive, motivation, social behaviour and motor function (Barrash,

Tranel & Anderson, 2000; Damasio & Van Hoesen, 1983; Lezak et al., 2004).

The basal ganglia, a bundle of nuclei comprised of the caudate, putamen and

globus pallidus, as well as the amygdala, subthalamic nucleus and substantia nigra, sits at

the base of the cerebral hemispheres. The caudate nucleus and putamen receive direct

input from the cerebral cortex, whereas the substantia nigra and the globus pallidus

project to the cerebral cortex via the thalamus (Lezak et al., 2004). Reductions in

cognitive flexibility (i.e., the ability to change cognitive strategies to meet new demands)

are noted after damage to the basal ganglia (Lawrence, Sahakian, Rogers, Hodge, & Tryptophan 20

Robbins, 1999). Collectively, these regions are innervated by serotonergic projections from the dorsal raphe nuclei (Graeff, 1997; Steckler & Sahgal, 1995).

Overall, certain aspects of executive functioning, such as novel solution

generation, have been found to improve with increased serotonin levels (Kurup & Kurup,

2003), whereas other functions, such as verbal fluency and strategy planning, have been

found to improve with decreasing serotonin levels (Park et al., 1994; Schmitt et al.,

2000). It is thus unclear from the literature the exact ways in which increases or

decreases in serotonin levels (as assessed via tryptophan manipulation) affect cerebellar,

basal gangliar, and frontal cortical functioning.

Emotional Regulation. Many different neuroanatomical structures are involved in

the processing, production and memory of emotionally-charged stimuli. The

hypothalamus, which is located just above the brain stem but below the thalamus,

influences the activity of the pituitary gland in order to control and coordinate such

activities of the endocrine and autonomic nervous systems as circadian rhythms, hunger,

thirst, fatigue and body temperature (Pinel, 2003; Rolls, 1999). Protective emotional

reactions such as fear or rage are also controlled by this structure (Lezak et al., 2004).

According to Flynn, Cummings and Tomiyasu (1988), depending on the location of the

hypothalamic damage, a myriad of symptoms may emerge, such as obesity or reductions

in drive or responsivity. Alterations in mood have also been implicated in damage to

hypothalamic pathways (Andreasen, 2001). Serotonergic innervation to the medial and

periventricular hypothalamus is received by dorsal raphe projections (Graeff, 1997;

Steckler & Sahgal, 1995), whereas the lateral hypothalamus receives medial raphe Tryptophan 21 projections (Graeff, 1997; Molliver, 1987). Thus, damage to these pathways would presumably reduce the amount of serotonin available to the hypothalamus.

Through its role as a relay station for the limbic system, the thalamus exerts an influence on emotional responding. It has been found that damage to the thalamus results in apathy, emotional flattening and reductions in drive (O’Connor, Verfaellie, & Cermak,

1995). The cingulate cortex, part of the limbic system, has also been implicated in emotional responding (Rolls, 1999). As stated above, the thalamus and the cingulate cortex are innervated by dorsal and medial raphe projections, respectively (Graeff, 1997;

Steckler & Sahgal, 1995).

The amygdala, which is also a component of the limbic system involved in emotional behaviour, has extensive innervation from the hypothalamus and is implicated in emotional responding (Lezak et al., 2004), processing and learning (Bechara, Damasio,

Damasio, & Lee, 1999). Through its connection to the ventral hippocampus, the amygdala also plays a role in memories of emotional events (Pinel, 2003). Lesions to the amygdala dampen the expression of emotional states and aggressive behaviour

(Aggleton, 1993; Brodal, 1981). Amygdalar lesions would also presumably decrease availability of serotonin in the brain, and it has been found that decreases in tryptophan, the precursor to serotonin, results in increased levels of aggression (Cleare & Bond,

1995; Pihl et al., 1995). The amygdala receives serotonergic innervation from dorsal raphe projections (Graeff, 1997; Steckler & Sahgal, 1995).

The basal ganglia are also implicated in emotional experiences, as it has been documented that bilateral damage to these structures results in flattening of emotional expression (Bhatia & Marsden, 1994). Damage to the circuitry of the non-motor Tryptophan 22

pathways of the basal ganglia are also implicated in several psychiatric disorders, including depression (e.g., Middleton & Strick, 2000b). As mentioned above, serotonergic innervation to the basal ganglia is via dorsal raphe projections (Graeff, 1997;

Steckler & Sahgal, 1995).

Fine Motor Control. The last area of functional neuroanatomy to be discussed in this section pertains to motor control. The pons, which literally means “bridge”, is a small structure on the brainstem above the medulla that is responsible for carrying sensory signal up to the thalamus, and for sending signals down from the cortex. It serves as a major pathway between the cerebellum and the cerebral cortex (Lezak et al.,

2004). Together, the pons and cerebellum are responsible for kinesthetic and postural control, fine-tuning motor impulses from the cerebral cortex (Lezak et al., 2004). These areas are innervated by dorsal raphe projections (Steckler & Sahgal, 1995). Damage to either area results in difficulty with coordination and fine motor control (Barlow, 2002;

Caplan, 2001). It has been reported within the literature that increased serotonin results in problems of motor coordination (e.g., Luciana et al., 2001) and slowed motor response time (e.g., Markus et al., 1998). Increased levels of serotonin may thus exert an inhibitory effect upon the pons and cerebellum, thereby reducing motor speed and response times (e.g., Luciana et al., 2001; Markus et al., 1998).

Serotonin, Mood and Cognitive Performance

As mentioned earlier, much of the research on 5-HT has focused on the role of serotonin in mental disorders and physiological disturbances. Indeed, serotonin has been implicated in many different disorders, such as depression (e.g., Sobczak et al., 2002), attention-deficit hyperactivity disorder (e.g., Barrickman, Noyes, Kuperman, Schumacher Tryptophan 23

& Verda, 1991), and sleep, arousal and insomnia (e.g., Lieberman et al., 1983), among others. Of the numerous disturbances in which 5-HT has been implicated, however, depression is a disorder commonly dealt with by clinical psychologists (Ormel, et al.,

1994). Thus, it comes as no surprise that there is a growing literature on the effects of depression on cognitive performance. For instance, it has been reported that depression can result in lower scores on measures of executive functioning (e.g., Rogers et al., 2004;

Veiel, 1997; but see Mitchell & Phillips, 2007), memory (e.g., Austin, Mitchell &

Goodwin, 2001), working memory (e.g., Harvey et al., 2004), speed of processing and motor performance (e.g., Gualtieri, Johnson & Benedict, 2006; Sobin & Sackeim, 1997), intelligence (e.g., Hartlage, Alloy, Vazquez & Dykman, 1993) and attention (e.g., Porter,

Gallagher, Thompson & Young, 2003). The mechanism behind this relationship between cognition and depression, however, is still somewhat unclear. It can be surmised that since depression is associated with reductions in serotonin levels (Frazer & Hensler,

1994), it could be that lower levels of tryptophan (or its metabolite, 5-HTP) are crossing the blood-brain barrier, resulting in lower levels of serotonin production and activity.

This could in turn directly affect the neuroanatomical structures that are known to play a role in a given cognitive function. For instance, it has been reported in the literature that reductions in hippocampal volume are frequently noted in those suffering from depression (e.g., Campbell, Marriott, Nahmias & MacQueen, 2004; Videbech &

Ravnkilde, 2004; but see Vythilingam, et al., 2004). Cortisol levels are often found to be elevated in those suffering from depression (e.g., Monteleone, 2001), and chronic elevation of cortisol is known to both reduce hippocampal activity and increase hippocampal atrophy (McAuley et al., 2009). Furthermore, stress is known to inhibit Tryptophan 24

hippocampal neurogenesis, a process that normally occurs throughout the lifespan, and to reduce dendritic branching (Jacobs, van Praag & Gage, 2000). Reductions in dendritic branching, as well as atrophy within the hippocampus, would both result in decreased

hippocampal volume. Thus, it could be that the lowered levels of serotonin, such as are

found in those with depressions (e.g., Wichers & Maes, 2002), affect memory via direct

effect on the hippocampus (and possibly other neuroanatomical structures involved in

this cognitive process).

According to Cook (1991), there is growing evidence to support such interactions

between serotonin, mood and cognitive performance. These processes likely occur in the

limbic system (described above), areas of the brain heavily innervated by serotonergic

projections. Further evidence of the relationship between serotonin and cognitive

performance lies within the hippocampus, a structure known to play a major role in long-

term memory (LTM). As described above, if the serotonergic pathways projecting to the

hippocampus are compromised, or if there is a change in the amount or rate of firing of

serotonergic cells, hippocampal functioning could be altered as a result. The thalamus,

which receives serotonergic projections from the dorsal raphe nuclei, is known to play a

role in attention (Corbetta et al., 1991) and thus, alterations in the activity of this pathway

or region could result in disruptions in information processing due to poor attention.

Taken together, the discussions in the previous two sections on functional

neuroanatomy and the relationship between mood, serotonin and cognition provide

evidence that many cognitive and affective processes are, in fact, affected by serotonin

and the serotonergic pathways known to affect neuroanatomical structures.

Tryptophan 25

Relationship between Serotonin, Depression and Antidepressants

As discussed above, depression is one of the most commonly seen psychological

disorders dealt with by clinicians. One way in which depression is treated is via

pharmacological intervention with antidepressant medications. There are three main

classes of antidepressant medications used in the treatment of depression. The oldest class is known as the tricyclic antidepressants and they exert their effects by blocking the reuptake of serotonin and norepinephrine. These actions on the serotonergic system are thought to regulate mood (Murray, 1998). Monoamine oxidase inhibitors (MAOIs) work by decreasing the rate at which the MAO enzyme breaks down monoamine neurotransmitters, thus increasing the availability of serotonin, dopamine, epinephrine and norepinephrine in the synapse. A third class of medication is known as the serotonin reuptake inhibitors. These drugs exert their influence by nonselectively inhibiting the uptake of serotonin and other monoamines, thereby increasing their concentrations in the synapse. The selective serotonin reuptake inhibitors (SSRIs), however, only block the reabsorption of serotonin, thus making them of the greatest interest here. Since the SSRIs work by blocking the reuptake of serotonin into presynaptic neurons, greater amounts of serotonin are available in the synapse (Murray, 1998). This increase in serotonin availability increases the inhibitory activity of presynaptic receptors, thereby decreasing the firing rate of the serotonergic neuron (Blier & de Montigny, 1994; Nutt et al., 1999).

This negative feedback mechanism results in an initial inhibition of the firing rate of the raphe nuclei. After this initial inhibitory period, the concentration of serotonin in the synapse begins to increase over the course of several weeks until serotonin levels reach therapeutic levels within the cortex (Nutt et al., 1999). There is documentation within Tryptophan 26

the literature that SSRIs are an effective treatment for depression (e.g., Kraft, Slager,

McGrath & Hamilton, 2005; Pallanti, & Sandner, 2007; Rossi, Barraco & Donda, 2004;

Zohar, & Westenberg, 2000; but see Hotopf & Barbui, 2004; Kirsch, Moore, Scoboria, &

Nicholls, 2002) as they have generally been found to improve negative mood states in

both normal, non-depressed persons, and in patients with depression (e.g., Barge-

Schaapveld, Nicolson, van der Hoop, & DeVries, 1995; Barton, et al., 2008; Bell,

Abrams, Nutt, 2001; Delgado et al., 1990). Of interest, however, is that there is research

documenting the efficacy of serotonergic precursors, such as 5-HTP, as being equal to

those of SSRIs in treating depression. For instance, Poldinger, Calanchini and Schwarz

(1991) conducted a clinical trial wherein patients diagnosed with depression where given

either 100mg of 5-HTP three times a day, or 50mg of the SSRI fluvoxamine three times a

day for a period of six weeks. At the end of the six-week trial, 5-HTP was not only found

to be as effective as the SSRI at treating depressive symptoms, but it also produced fewer

side effects. These results echo those of van Praag (1981) who similarly found in his

study that daily doses of 200mg of 5-HTP were as effective as the tricyclic antidepressant

clomipramine at alleviating symptoms, again with fewer side effects. Further support for

these findings comes from the literature on acute tryptophan depletion and SSRI use. For

instance, Delgado and colleagues (1990) induced acute tryptophan depletion in a group of

patients diagnosed with depression who were being successfully treated with SSRIs. Of

the 21 patients in this study, two-thirds of them experienced a relapse in their depressive

symptoms following tryptophan depletion. Upon consuming a normal meal, it took

between 24 and 48 hours for remission to return. The authors found that free plasma

tryptophan levels were negatively correlated with depression scores during the depletion, Tryptophan 27

with more tryptophan in the plasma resulting in lesser degrees of depression. These

results have been replicated in the literature by several other researchers (e.g., Booij, Van

der Does, Haffmans, & Riedel, 2005; Nutt et al., 1999; O’Reardon et al., 2004) which,

when taken together with the literature on SSRIs, indicates that reductions in serotonergic

activity may be implicated in depressive symptoms in certain groups of people (Cooper et

al, 1996).

The relationship between serotonin and depression, however, is far from clear as

there is documentation within the literature that selective serotonin reuptake enhancers

(SSREs) such as tianeptine, which act to increase the reuptake of serotonin at the

synapse, also result in improvements in symptoms of depression (Defrance, Marey &

Kamoun, 1988; Mennini, Mocaer & Garattini, 1987). Thus, although it is unclear whether increases or decreases in serotonergic activity have greater implications for the treatment of depression, it does appear that serotonin is in some way involved in

depressive symptoms.

Effects of Other Tryptophan Metabolites on Brain Function

There is also growing evidence, however, that other metabolites of tryptophan

affect neuroanatomical function and thus, cognitive performance. Such metabolites are

created when tryptophan circulating in the bloodstream passes through the liver, which

can result in one of four possible outcomes: 1) tryptophan is returned, unchanged, into the

bloodstream for use elsewhere in the body; 2) liver enzymes break tryptophan down into smaller proteins; 3) tryptophan gets converted into 5-HTP; or 4) tryptophan is converted into kynurenine (Murray, 1998). As kynurenine is a convulsant responsible for proper

muscle function, an excess of kynurenine can result in damage to the muscles. Normally, Tryptophan 28 the liver produces greater quantities of kynurenine (used in the production of niacin) than

5-HTP. However, heightened or chronic stress can upset the balance even more by decreasing the supply of the enzyme necessary to produce 5-HTP, resulting in even less

5-HTP being produced and thus lowering the production of 5-HT in the brain (Murray,

1998). Kynurenic acid, which is produced by the kynurenine pathway and released by astrocytes, is critical for memory and learning (Potter, 2009). This is because the hippocampus is heavily innervated by glutamatergic neurons and glutamatergic neurotransmission is mediated by NMDA (N-methyl-D-aspartate) receptors. Kynurenic acid acts as an NMDA receptor antagonist, meaning that it reduces the chances that the calcium ion channel (which is controlled by NMDA) will open. The opening of this channel is essential for long-term potentiation (i.e., the protracted increase in communication that occurs between the pre- and the post-synaptic neuron when they are stimulated at the same time) (Carlson, 2007), which is, in turn, thought to be a major underlying mechanism in learning and memory (Bliss & Collingridge, 1993). Thus, greater amounts of kynurenine result in less 5-HTP in the brain, leading to less serotonin production in the brain, but more kynurenic acid, an NMDA antagonist the makes it less likely that long-term potentiation will occur. Together, these processes reduce both learning and memory within the hippocampus.

The NMDA receptors are also thought to play a role in developmental neural plasticity (Cooper et al., 1996). These receptors have agonist receptor sites for glutamate and for glycine, both of which must be activated if the ion channel is to open (Dingledine

& McBain, 1994). However, kynurenic acid by-products, such as quinolinic acid, act as antagonists of the glycine receptor site (Dingledine & McBain, 1994), working to Tryptophan 29

decrease the chances of the NMDA-regulated ion channel opening, and thereby

decreasing the likelihood of long-term potentiation occurring. Quinolinic acid is an

excitatory neurotoxin, meaning that it binds to a neuron and causes damage or cell death

due to its stimulation. In this way, quinolinic acid may play a role in neurotoxicity

induced by NMDA (Cooper et al., 1996). Quinolinic acid has also been implicated in

neurodegeneration within the rat hippocampus, resulting in cognitive impairment

(O’Neill, Morgan, & Brioni, 1998). Fortunately, glial cells release kynurenate, a by-

product of kynurenine, to serve a neuroprotective role within the brain (Cooper et al.,

1996). It can thus be seen that the different by-products of tryptophan metabolism have

differing effects on the neurochemistry of the brain. Quinolinic acid, a neurotoxin, may

produce memory impairments, whereas kynurenate works to protect the brain from these

neurotoxic effects. If there is an imbalance in these neurochemicals, the chances of long-

term potentiation and thus learning and long-term memory, may be decreased.

Lastly, there is some evidence that melatonin, another tryptophan metabolite, plays a role in cognitive functioning. Melatonin is created in the pineal gland, which houses all the necessary enzymes to turn tryptophan into serotonin; serotonin is then converted into melatonin (Frazer & Hensler, 1994). Aside from its role in circadian rhythms, melatonin has been implicated in the inhibition of long-term potentiation in the

rat hippocampus (Soto-Moyano et al., 2006) and in deficits in learning and memory in

mice (Larson et al., 2006). Thus, if there are alterations in the amount of tryptophan

reaching the brain, a ripple effect could be seen wherein less serotonin is created,

resulting in less melatonin, which in turn could lead to decreased performance on

learning and memory tasks. Tryptophan 30

Taken together, it is clear within the literature that there are many different

pathways in which tryptophan can affect the neurochemical balance in the brain which

may in turn produce changes in cognitive performance by way of influencing

neuroanatomical functioning.

Effects of Tryptophan Augmentation or Depletion on Neuropsychological Performance

Amino Acid Protocol

One method of assessing the effects of tryptophan metabolites on affect and

cognitive performance is via acute tryptophan depletion. As discussed previously,

depletion works by decreasing the tryptophan:LNAA ratio, resulting in marked decreases

of tryptophan compared to the LNAAs competing for transport across the blood-brain

barrier. By depleting tryptophan levels, researchers can quantify and measure the effects

of lower tryptophan levels on cognition. The most common means of accomplishing depletion is by ingesting a mixture of amino acids (prepared as a drink) containing all the essential amino acids except for tryptophan. The balanced, or placebo, condition in such studies sees the addition of L-tryptophan to the depletion mixture. In studies that include acute tryptophan augmentation, a larger dose of tryptophan is added to the mixture than that added for the balanced drink. At this point, a note on the terminology used within the literature is necessary as there are several terms that are used almost interchangeably when referring to acute tryptophan depletion (e.g., ATD, protein-loading) or to acute tryptophan augmentation (e.g., ATA, carbohydrate-loading). For parsimonious reasons, the remainder of this paper will employ the term ‘depletion’ to denote ‘acute tryptophan depletion’ or ‘protein-loading’, and the term ‘augmentation’ will be used to refer to Tryptophan 31

‘acute tryptophan augmentation’ or ‘carbohydrate-loading’. The term ‘balanced’ will be

used in reference to the ‘balanced condition’.

Among the first to examine the effects of acute tryptophan depletion were S. N.

Young and colleagues (S. N. Young, Smith, Pihl & Ervin, 1985), who found marked

decreases in free and total plasma tryptophan levels following ingestion of the depletion

mixture, and drastic increases following ingestion of the balanced drink. This method

has since been employed by numerous researchers who have found similar results when

examining the effects of depletion on total and/or free plasma tryptophan levels (e.g.,

Hughes et al., 2003; Schmitt et al., 2000). With evidence that this protocol produced

reliable alterations in plasma and total free tryptophan levels, attention was turned to the effects such manipulations would have on mood and cognition given that alterations in plasma tryptophan levels would presumably result in an alteration in brain serotonin production and release.

In order to examine the effects of depletion on memory and learning, Park and colleagues (1994) recruited 12 male participants and randomly assigned them to a depletion or to a balanced group. Both researchers and participants were blind to the drink composition, and all participants took part in both conditions separated by a minimum of 7 days between test sessions. On both occasions, participants were provided with a 52 g amino acid drink (S. N. Young and colleagues (1985) employed a 100 g protocol), and blood samples were drawn both before ingesting the drink and approximately 4 hours later, just prior to commencing the neuropsychological testing.

The domains of executive functioning, visual/visuospatial pattern learning and memory, attention, and working memory were tested using the Cambridge Neuropsychological Tryptophan 32

Test Automated Battery (CANTAB), a computerized neuropsychological test battery.

Participants also completed visual analogue scales to measure their perceived level of sadness, anxiety, irritability, concentration, and energy levels, along with a computerized test of autobiographical memory. Researchers found that total free and plasma tryptophan levels were lowered following the depletion condition, but remained the same following the balanced condition. Overall, it was found that although neither mood nor autobiographical memory was affected by depletion, certain types of learning and memory (i.e., learning and remembering new rules and visuospatial pairings) were reduced by depletion. In addition, neither attention nor working memory showed any effect of depletion. The authors concluded that low tryptophan levels result in poor consolidation of information in memory and thus lower scores on measures of long-term memory (LTM) and learning.

The finding that depletion results in transient decreases in learning has been corroborated by several others. For instance, using the same protocol as S. N. Young’s group (S. N. Young et al., 1985), Rogers and colleagues (1999) found reductions in visual discrimination learning following depletion (compared to a balanced condition), with participants demonstrating marked difficulty learning new stimulus-reward pairings.

In this study, participants’ ability to shift attention to now-relevant stimuli dimensions remained intact. In addition, both total and free tryptophan levels were lowered by the depletion but not by the balanced protocol. These results were interpreted to suggest that cortical and subcortical regions undergo a change in neuromodulation that is affected by serotonin (Rogers et al., 1999). Tryptophan 33

Transient decreases in LTM have also been noted by Riedel and colleagues

(1999), who examined mood and cognition in tryptophan-depleted participants with and

without a family history of depression. Using S. N. Young’s protocol (1985), Riedel and colleagues found that, compared to a balanced condition, depletion resulted in lower scores on tests of LTM. More specifically, reductions in delayed recall and recognition response time and sensitivity were apparent 6 hours after ingesting the drink. No effects were found on perception, motor function, or short-term memory 6 or 24 hours after the initial drink, despite participants receiving 10 g booster portions 7, 11 and 13 hours after the initial ingestion of the drink and the low-tryptophan meals at lunch and dinnertime.

Further, although no differences were found between groups with and without a family history of depression on the neurocognitive tests, depletion did produce lower moods in those with a family history of depression, a finding similar to that of Benkelfat and colleagues (1994). It should be noted, however, that 7 female participants (four of whom were in the depletion condition) withdrew from Riedel’s study due to nausea induced by the amino acid drink (three of whom vomited). This point highlights the fact that the amino acid mixture is not only extremely potent, but also highly unpalatable, which

increases the odds of protocol-induced confounds within the study. For instance, it is

possible that even mild or unreported nausea may affect cognitive performance, making it

more difficult to discern true effects from those produced by objectionable testing

procedures. The disagreeable taste of the amino acid mixture has been reported by

several other researchers (e.g., Greenwood, Lader, Kantameneni, & Curzon, 1975;

Hughes et al., 2000; Park et al., 1994; Riedel et al., 1999), many of whom have tried to

improve its taste by mixing flavoured concentrates or chocolate syrup into the drink. Tryptophan 34

Nonetheless, regardless of the palatability of the protocol, the literature seems to suggest

that depletion results in reductions in LTM and has the potential to influence mood,

particularly in those who are susceptible to depression (Benkelfat et al., 1994).

The effects of depletion on attention, however, are not as clear. For instance,

using the same amino acid mixture employed by Park’s group (1994), Coull and

colleagues (1995) examined the effects of depletion on emotional selective attention as

measured by a focused attention task and an attentional searching task. On both tasks, the

words “left” or “right” served as targets, and the distractors were words selected from

four groups of words with emotional valence (e.g., “choke” or “panic”). The attentional

searching task added a component of compatibility such that compatible trials were those

in which the target word “left” (or “right”) appeared on the left side (or the right side,

respectively) of the computer screen; incompatible trials were those in which the targets

did not match the side of the screen on which they were presented (i.e., the word “left”

appeared on the right-hand side of the screen). As with other studies employing acute tryptophan depletion, participants took part in both the depletion and the balanced conditions, with no less than 1 week between testing sessions. On both occasions, testing began 4 hours after ingesting the drink. The authors concluded that depletion did not affect focused attention, but they reported shorter response latencies when stimuli were incompatible on the attentional search task; emotional valence did not affect this relationship (Coull et al., 1995).

These findings are at odds with those of Schmitt and colleagues (2000), who administered a comprehensive neuropsychological battery to determine the effects of depletion on executive functions, memory, language, processing speed, mood, and Tryptophan 35 attention. They used the 100 g protocol and administered a 10 g maintenance dose 6 hours later. All participants took part in both the depletion and balanced conditions, which were separated by at least 7 days; blood samples were collected at multiple times on both days. Overall, Schmitt’s group found that although depletion did not affect planning (bolstering the findings of Park et al., 1994), processing speed, or divided attention, it did produce significant improvements in both auditory and visual focused attention. A possible reason for the divergence in findings is that whereas Coull and colleagues (1995) utilized the same amino acid mixture as Park’s group (52 g), Schmitt’s group utilized the protocol employed by S. N. Young and colleagues (100 g) and included maintenance doses. It is likely that the greater dose of each amino acid, as found in the 100 g mixture, results in greater “depletion” of tryptophan as the levels of the other LNAAs increase and crowd out tryptophan for transport across the blood-brain barrier. The higher dose of amino acids ostensibly results in greater cognitive changes.

Schmitt’s group reports that, compared to the balanced condition, plasma tryptophan levels dropped 64% from baseline and the tryptophan:LNAA ratio fell by 33% from baseline 9 hours after ingesting the drink. Coull’s group, on the other hand, did not report the drop in plasma tryptophan levels attained by their manipulation. However, as Coull employed the same protocol as Park and colleagues, it is likely that plasma and total free tryptophan was similarly drastically decreased. Of note, however, is that neither Park’s,

Coull’s, nor Schmitt’s group altered the amount of the amino acid mixture based on participants’ body mass. Indeed, it seems that the norm within the literature is to provide all participants, regardless of gender or body mass, with the same quantity of the amino acid mixture (but see Fischer et al., 2002). While it is not doubted that these variables Tryptophan 36

may affect the degree to which tryptophan levels are altered, the fact that most studies do

not control for these confounds makes generalization of these findings quite difficult.

Schmitt’s group also found that verbal fluency scores improved 5 hours following ingestion of the depletion mixture (compared to baseline measures), supporting the notion that serotonin is important for proper frontal lobe functioning. This conclusion is based on the fact that verbal fluency tasks result in increased activation in the frontal lobes during imaging studies (Brannen et al., 2001). Further, Schmitt’s results corroborated

Park’s (1994) assertion that serotonin reduces certain aspects of learning and memory as they found evidence of decreased LTM memory in light of spared short-term memory and retrieval abilities. An interesting point, however, is that Schmitt and Park both found reductions in LTM despite using different volumes of the amino acid mixture (100 g versus 52 g, respectively), suggesting that decreases in LTM are robust findings regardless of the degree of serotonin depletion. Schmitt and colleagues point out, however, that although Park’s group did find selective reductions in learning and memory

(as measured by the number of trials needed to learn spatial locations on a paired associates learning task), they failed to find such effects on any of the actual memory tests that were employed. Schmitt’s group suggests that this is due to the fact that the memory tests utilized by Park’s group did not measure memory for material learned and consolidated after a considerable delay. For this reason, Schmitt’s group makes the point that, “[M]emory tests which do not incorporate delayed assessment or do not require long-term storage of new information are likely to fail to detect memory deficits of acute tryptophan depletion” (p. 27). Tryptophan 37

Few of the studies discussed thus far have included a neuropsychological test

battery as comprehensive as that employed by Hughes and his colleagues (2003) in their

efforts to examine the effects of tryptophan depletion on mood and cognitive functioning.

In contrast to Schmitt’s group (2000), whose battery contained several computerized tests

and experimental tasks, Hughes’ battery assessed a wide range of domains, including

attention and executive functioning, verbal learning and memory, visuospatial learning

and memory, and mood, using both paper-and-pencil and CANTAB tests. A group of 20 males were tested using the 52 g drink protocol; each participant took part in both the depletion and the balanced conditions, with no less than 7 days between testing sessions.

On each test day, blood samples were drawn at four separate times, and testing began 4 hours after ingesting the initial drink. Analysis of the blood assays showed that there were no significant between group differences in baseline measures of either total plasma or free tryptophan levels. For the depletion condition, both total plasma and free tryptophan decreased over time, remaining at depletion levels of 60.7% and 56.9% at 330 minutes, respectively. For the balanced condition, however, total tryptophan increased by 33.6% at 240 minutes, but was depleted to a level of 6.8% below baseline by 330 minutes. Free tryptophan levels were increased by 71.8% at 240 minutes, but had reduced to 28.5% by 330 minutes time. Taken together, these findings demonstrate that the manipulation successfully altered total plasma and free tryptophan levels.

Nonetheless, test results showed that the tryptophan manipulation failed to produce any decline in cognitive functioning or any changes in mood. These findings stand in stark contrast to the literature discussed previously in that several researchers have detected poorer performance within these same domains. Bolstering Hughes’s findings, however, Tryptophan 38

are those of Shansis and colleagues (2000) who similarly found no effect of depletion on

mood, attention, and memory using a healthy male sample. Shansis’ team suggested that

the discrepancy between their findings and those of others (e.g., Park et al., 1994) could be due to the testing instruments employed. That is, Park’s group used the Cambridge

Neuropsychological Test Automated Battery, which is known to be sensitive to subtle neuropsychological (i.e., cognitive) changes (Shansis et al., 2000), whereas Shansis used paper-and-pencil tests. However, unlike Shansis’ group, Hughes’ group employed three of the same measures from the battery employed by Park’s group: the Tower of London,

Attentional Set-shift, and the Paired Associates Learning tests. Thus, while it is possible that Shansis did not select measures that are sensitive enough to detect subtle cognitive changes brought on by depletion, it does not explain why Hughes, who administered the same protocol as Park and who also had a larger sample size than Park, found no significant results. As Hughes and colleagues point out, the failure to measure delayed memory or recognition, the degree of tryptophan (and thus serotonin) depletion or disruption, and any individual differences in the degree of sensitivity to depletion, including gender or body mass, or some combination of these factors may be responsible for the inconsistency of findings.

Regardless of the contradictory findings, the common factor between all of the studies discussed thus far is that they have only examined depletion in comparison to a

balanced condition; that is, not a single one of these studies employed an augmented

condition. The administration of an augmented condition is important as it enables us to

learn about what happens when we raise tryptophan concentrations to abnormally high

levels and the effects that this has on cognitive functioning. To overcome this gross Tryptophan 39 oversight, Luciana and colleagues (2001) conducted one of the only studies found for this review that examined cognitive functioning by employing both a depletion and an augmentation condition (no balanced condition was used). Using S. N. Young’s (1985)

100 g amino acid protocol, participants took part in both conditions, separated by a minimum of 7 days. Assessing the domains of working memory, executive functioning, short-term memory and attention, and motor speed and accuracy, Luciana’s group found several interesting differences between the depletion and the augmented groups. For instance, although both conditions lowered participants’ scores of positive affect (as measured by the PANAS; Watson, Clark, & Tellegen, 1988), the depletion group exhibited faster response times on the Grooved Pegboard Test, more digits correct on the backward trial of the Digit Span test, and better ability at processing sad affective content compared to the augmented group. Conversely, although the augmentation group exhibited decreased motor coordination (as evidenced by the number of drops on the

Grooved Pegboard Test), they made fewer errors of omission on a letter-cancellation test.

No discernable differences were found between the two groups on the Digit Span forward trial, Spatial Span, verbal fluency, or spatial working memory. In both the depletion and augmentation conditions, total plasma tryptophan concentrations were significantly lowered and raised, respectively, compared to baseline levels. Overall, the authors concluded that augmentation results in transient reductions in affective and verbal working memory (as measured by the Digit Span Backward trial), as well as decreased motor-coordination while sparing (and even enhancing) immediate vigilant attention.

Taken together, Luciana’s group concluded that these findings are consistent with the notion that increased serotonin activity results in a reduction of the flow of information, Tryptophan 40

leading to declines in motor coordination, working memory, and short-term attention.

Perhaps more importantly, results of this study demonstrate that just as depletion effects

performance, so too does augmentation, highlighting the necessity of researchers

including an augmented condition in future research to further our understanding of the

effects of augmentation on neuropsychological performance.

Overall, it is clear that there is considerable controversy and contradiction within

the literature on the effects of depletion and augmentation. This seems to be related to the

following factors: a) the tests selected for use in the study, many of which do not always

correspond with the instruments most widely used in clinical settings; b) the use of amino

acids, which often result in adverse effects such as nausea or vomiting; c) gender ratios,

which are rarely equal, especially as many studies only include males or provide no

information on gender distributions; and d) high attrition rates and small sample sizes,

making generalization of test results difficult. In an attempt to address some of these

issues (e.g., nausea and small sample sizes), researchers have begun to look to other

methods of altering tryptophan (and thus serotonin) levels, the most common of which is

the administration of carbohydrate-rich, protein-poor meals.

Dietary Manipulations

The effect of diet on brain serotonin levels is also unclear as there are many

factors influencing whether tryptophan will increase brain serotonin production or

release. As discussed previously, merely ingesting tryptophan-rich foods does not necessarily alter brain- serotonin levels as it could get metabolized before it can cross the blood-brain barrier, or prevented from easily crossing the blood-brain barrier due to competition from the other LNAAs. This is because the volume of the LNAAs also Tryptophan 41

increase due to the ingestion of dietary proteins, thereby reducing the tryptophan:LNAA

ratio. Ingesting carbohydrates in a protein-poor meal, however, appears to avoid both issues by increasing insulin, thereby sweeping the LNAAs into the surrounding tissues and allowing tryptophan to easily cross the blood-brain barrier to aid in the synthesis of serotonin.

Using the dietary method of altering tryptophan levels, Markus and colleagues

(1998) studied the effects of carbohydrate-rich meals (designed to augment tryptophan levels) in comparison to protein-rich meals (designed to deplete tryptophan levels) on

mood and memory in stress-prone participants during a stress-inducing task. Participants

were divided into two groups, high-stress (n = 24) and low-stress (n = 24), based upon

their scores on the Inadequacy Scale of the Dutch Personality Inventory (Luteijn, Starren,

& van Dijk, 1975). All participants were randomly assigned to start with either the

carbohydrate-rich/protein-poor meal, or the protein-rich/carbohydrate-poor meal. Each

participant took part in both conditions, which were separated by a 4-week period. On

each testing day, participants ate breakfast upon arriving at the testing site, followed by a

snack 1.25 hours later. Lunch was served 45 minutes after consumption of the snack.

The test battery, which was administered 1.5 hours after lunch, was preceded by the

collection of a blood sample. The battery consisted of the Profile of Mood States, a stress

induction task (a mental arithmetic task completed during noise interference), and a

computerized memory scanning task measuring accuracy and response times. The first

main effect Markus’s group reported was that the ingestion of the carbohydrate-rich diet

increased the tryptophan:LNAA ratio, rising from 0.074 on the protein-rich test day to

0.105 on the carbohydrate-rich day. They also reported that regardless of stress group, Tryptophan 42

the carbohydrate-rich meal resulted in slower reaction times on the computerized

memory task. The authors concluded that the ingestion of carbohydrates increased brain

tryptophan levels, and thus that the synthesis and activity of brain serotonin was also

increased. They noted that this, in turn, resulted in slowed response times. Thus, their prediction that a carbohydrate-rich meal would protect stress-prone people from deteriorations in mood and cognitive performance in the face of a stressful task was met.

Markus and colleagues assert that increased serotonin synthesis and activity likely mitigated the stress-response of the high stress group by increasing their sense of control in an otherwise uncontrollable situation (the stress-induction task). The general conclusion to be drawn from this study, however, is that carbohydrate-loading increased the tryptophan:LNAA ratio in a similar manner as the amino acid protocol, and neurocognitive effects were observed as a result. Thus, it seems that the dietary method can be used as an alternative to the amino acid protocol as a means of altering the rate of production and release of serotonin.

The utility of manipulating diet to measure the effects of varying macronutrients on performance and mood has been shown by many other researchers. For instance, to study the effects of tryptophan augmentation, Lieberman et al., (2002) provided 143 US

Army soldiers with one of three carbohydrate drinks: 6% by volume, 12% by volume, or a placebo mixture, all of which looked and tasted identical. This was a between-subjects study, with each soldier assigned to only one condition. No blood samples were collected.

The soldiers engaged in several physically demanding tasks throughout the day while wearing vigilance monitors (specialized watches). When soldiers heard the monitors beep, they had to respond as quickly as possible by pressing a button on the monitors. Tryptophan 43

Response times were utilized as an indication of vigilance. Profile of Mood States mood

questionnaires were also completed at three separate times throughout the day. The

authors found dose-related increases in sustaining vigilance and alertness, such that those

in the 12% per volume group performed the best and those in the placebo group

performed the worst, declining in vigilance at every designated test period. Dose-related

effects were also found for confusion on the Profile of Mood States, wherein those in the

placebo group scored as more confused than either of the carbohydrate groups, with the

12% group being the least confused. The authors conclude that during times of sustained physical activity, carbohydrates aid in the maintenance of vigilance and enable optimal cognitive functioning.

The finding that carbohydrates enhance attention and decision times, however, has not been replicated by all researchers. In a study by Fischer and colleagues (2002), participants were randomly assigned to one of three dietary groups: high- carbohydrate/low-protein (i.e., augmentation), low-carbohydrate/high-protein (i.e., depletion), or a balanced condition. All participants took part in each condition, with exactly 1 week separating each test condition. In each case, the cream-like meals were identical in taste, texture, and colour. Blood samples were collected and the cognitive domains of motor performance, information processing, short-term memory and peripheral attention were assessed. Overall, the authors found that cognitive performance, especially short-term memory, was greatest following the high-protein meal

or the balanced meal, whereas the high-carbohydrate meal resulted in the poorest

performance, producing only transient improvements in attention and decision times. Tryptophan 44

Neither the carbohydrate nor the protein meal affected peripheral attention, which the

authors credited to a lack of sensitivity of the measure employed.

However, comparing protein (a depletion method) and two carbohydrate meals

(one high in starch and one high in sugar, designed to augment tryptophan levels), Smith,

Leekam, Ralph, and McNeill (1988) found that the carbohydrate meals resulted in slowed response times to peripheral targets whereas the protein meal resulted in greater distractibility on a centralized target-detection task. In addition, there were no overall effects of meal composition on attention or mood. Taken together, these findings suggest

that protein increases vigilance and alertness compared to carbohydrates.

It has been found, however, that the effects of carbohydrates on performance

differ depending on age and gender. For instance, Spring, Maller, Wurtman, Digman,

and Cozolino (1983) examined the effects of protein and carbohydrates on a group of

younger (aged 18-39 years) and older (aged 40-65 years) participants, each of whom

were assigned to one of four groups: high-protein breakfast, high-protein lunch, high-

carbohydrate breakfast, or high-carbohydrate lunch. Utilizing the Stanford Sleepiness

Scale, the Profile of Mood States, visual analogue mood scales, an auditory response time

task and a dichotic shadowing task measuring information processing of sustained and

selective attention, they found significant effects for meal type, gender, and time of the

meal. That is, those who consumed the high-protein meal performed with greater

accuracy on the dichotic shadowing task, whereas there was no effect of meal on the

auditory response time task. However, compared to the protein meals, the carbohydrate

meals produced a greater feeling of sleepiness in women than in men, and a greater sense

of calmness in men than in women. Furthermore, the protein meal resulted in those in the Tryptophan 45 older age group feeling more tense and less calm if it was ingested at breakfast time, whereas performance was worse on the dichotic shadowing task (i.e., sustained selective attention) following carbohydrates at lunchtime. The authors concluded that the consumption of a high-carbohydrate lunch affected concentration in older participants, likely resulting from faltering attention.

In an older sample of adults, however, Kaplan, Greenwood, Winocur, and

Wolever (2001) found that carbohydrates, as well as protein and fat, improved several aspects of cognition in individuals 61-79 years of age. In this study, each participant took part in all four conditions, ingesting one drink (protein, carbohydrate, fat or placebo, 300 mL each) every 3-7 days. Within 15 minutes of consuming the drink, participants were administered three verbal memory tests: a list-learning task (testing immediate recall), and both an immediate and a delayed paragraph recall test. As fillers during the delay period, the Trail Making Test (Reitan, 1958) and an attention task were completed. All three drinks (save for the placebo) were found to improve delayed paragraph recall, with a trend towards improved immediate recall. More specifically, the carbohydrate drink was found to improve performance on the Trails task and delayed paragraph recall in men, whereas the protein drink resulted in greater immediate paragraph recall and the fat drink improved attention. Since all three drinks aided in increasing memory, the authors concluded that all three macronutrients likely exert different effects upon cognitive function.

Thus, it should be clear that the neuropsychological effects of tryptophan are varying and contradictory, especially when differing methodologies (i.e., amino acid protocol or dietary protocol) and manipulations (i.e., depletion or augmentation) are Tryptophan 46

considered. For instance, recall that Coull and colleagues (1995) found no effect of

depletion on attention using the 52 g amino acid protocol, whereas Schmitt’s group

(2000) found that focused attention improved with the ingestion of a depletion 100 g

protocol drink. Luciana and colleagues (2001) found that a 100 g augmentation mixture

resulted in better attention than a 100 g depletion mixture. However, Hughes’s team

(2003) found that depletion using the 52 g protocol had no effect on any domain of

cognitive functioning. Within the dietary manipulation literature, Markus’s research group (1998) found that carbohydrates reduced response times, a finding in direct contradiction to that reported by Lieberman’s group (2002). Despite such inconsistencies, however, there do appear to be several relatively reliable findings due to tryptophan manipulation. It appears that depletion, produced either via the amino acid protocol or the carbohydrate manipulation, is related to declines within the areas of LTM

(Park et al., 1994; Riedel et al., 1999; Rogers et al., 1999) and mood (in susceptible individuals) (Luciana et al., 2001; Riedel et al., 1999; but see Hughes et al., 2003 and

Shansis et al., 2000), with mixed results for effects on attention (Coull et al., 1995;

Hughes et al., 2003; Lieberman et al., 2002; Schmitt et al., 2000; Shansis et al., 2000), response time (Lieberman et al., 2002; Markus et al., 1998) and verbal fluency (Schmitt et al., 2000). Conversely, augmentation seems to result in transient reductions in affective and verbal working memory, as well as motor coordination, while enhancing immediate vigilant attention (Luciana et al., 2001) (see Table 1 for summary of findings in the literature).

Tryptophan 47

Table 1

Summary of Selected Findings Within the Literature

Research Group Manipulation Design Conditions Effect of Findings Method Employed

Park et al., 1994 amino acid within depletion & depletion - no effect on mood n = 12 M balanced - lower scores on LTM

Rogers et al., 1999 amino acid between depletion & depletion - reductions in visual discriminant n = 31 (15 M) balanced - intact ability to shift attention

Riedel et al., 1999 amino acid mixed depletion & depletion - reductions in LTM scores n = 27 (12 M) balanced - lower mood in those with family history of depression

Coull et al., 1995 amino acid within depletion & depletion - no effect on attention n = 12a balanced

Schmitt et al., 2000 amino acid within depletion & depletion - no effect on planning, processing n = 20 (10 M) balanced speed or divided attention - improvements in auditory and focused attention - delayed improvements in verbal fluency - reductions in LTM scores

Hughes et al., 2003 amino acid within depletion & depletion - no reductions on scores in any n = 20 M balanced neuropsychological domains - no reductions in mood scores Tryptophan 48

Shansis et al., 2000 amino acid within depletion & depletion - no reductions in mood, attention or n = 12 M balanced memory scores

Luciana et al., 2001 amino acid within depletion & depletion - faster response times n = 19a augmentation vs. - improvements in working memory augment. - improvements in processing sad affect

augment. - reductions in affective processing vs. - reductions in verbal working depletion memory - decreased motor coordination - enhanced vigilant attention

Markus et al., 1998 diet mixed depletion & augment. - slower response times n = 48 (13 M) augmentation

Lieberman et al., 2002 diet between augmentation & augment. - improvements of vigilance & n = 143 M balance attention - lower scores on confusion ratings

Fischer et al., 2002 diet within augmentation, depletion - improvements in STM n = 15 M depletion & & balanced balanced

augment. - transient improvements in attention and response times

Tryptophan 49

Smith et al., 1988 diet within augmentation augment. - slower response times n = 11 (5 M) & depletion

Spring et al., 1983 diet between augmentation augment. - greater feeling of sleepiness in n = 184 (129 M) & depletion women - greater feeling of calmness in men - poor performance on dichotic shadowing task (at lunch only)

depletion - greater accuracy on dichotic shadowing task - greater feeling of tenseness and reduction in feelings of calmness in older adults (at breakfast only)

Kaplan et al., 2001 diet within augmentation, augment. - improved delayed paragraph recall n = 22 (11 M) depletion, - improvements in Trail Making Test balanced & fat

depletion - improved delayed paragraph recall - greater immediate paragraph recall

balanced - no effect

fat - improved delayed paragraph recall improved attention

a = no gender information provided Tryptophan 50

Purpose and Hypotheses of the Present Study

The purpose of this study is to examine the effects of tryptophan on neuropsychological performance. Thus, the following hypotheses have been made:

Hypothesis 1: Depletion will result in lower scores on measures of LTM;

Hypothesis 2: Depletion will result in lower mood scores;

Hypothesis 3: Augmentation will lead to lower scores on measures of working

memory;

Hypothesis 4: Augmentation will result in functional improvements within the

areas of attention and vigilance;

Hypothesis 5: The balanced group will score higher than the depletion group on

verbal LTM and on mood indices, and higher than the augmentation

group on verbal working memory;

Hypothesis 6: The balanced group will score lower than those in the augmentation

group on tests of attention and vigilance;

Exploratory analyses will also be conducted in order to examine any group differences

that may arise on items comprising the composite attention and working memory scores,

as well as any differences on the individual items of the PANAS.

The benefits of employing a dietary manipulation outweigh those of the amino

acid protocol for several reasons. First, it is easy to attain the necessary materials – they

are all readily available at any local grocery store. Second, it is affordable for most

researchers and requires no special equipment or access to resources. With the amino

acid protocol, each individual amino acid powder must be purchased separately and then

mixed in the appropriate amounts. Using the dietary method, foods can be purchased Tryptophan 51 fresh, and possibly even in bulk, and stored in a refrigerator until needed. Third, it is better tolerated by participants, with lower chances of experiencing ill-effects (e.g., nausea, vomiting, etc.). Fourth, it is less aversive (Vered et al., 2001) given that participants are taking part in an activity (eating food) not typically associated with stress and anxiety. Lastly, it has potentially important implications for improving transient or occasional cognitive, physiological, or affective problems, including furthering our understanding of “emotional eating”.

Unlike the present study, the majority of research within the literature does not include an augmented, a depleted and a balanced meal condition (e.g., Coull et al., 1995;

Park et al., 1994; Rogers et al., 1999). Although Fischer and colleagues (2002) similarly employed all three conditions in the form of “cream-like” meals, all 15 of their participants were male. As the present study included both males and females, it will enable us to better tease apart the effects of tryptophan on neuropsychological performance for both males and females. What is more, many studies within the literature (e.g., Fischer et al., 2002; Rogers et al., 1999; Smith et al., 1988) do not include a comprehensive neuropsychological battery comprised of tests and measurements that are widely used within clinical settings; the present study does include such a battery, allowing for greater ecological validity. The present study also included the administration of commonly consumed foods, as opposed to the potent and potentially aversive amino acid mixtures used by some researchers (e.g., Riedel et al., 1999; Schmitt et al., 2000), allowing for further ecological validity. Lastly, although the majority of the research within the literature has employed within-subjects designs (e.g., Hughes et al.,

2003), many have noted high attrition rates due to repeated testing sessions or reactions Tryptophan 52

to the amino acid protocol (e.g., 26% attrition rate in Riedel et al., 1999). Further, although a within-subjects design allows for comparison within the same participant across all three conditions, thereby eradicating such between-subject confounds as individual differences, it does introduce the possibility of such confounds as practice effects due to repeated testing, test expectancy, order effects (of test condition), fatigue and attrition, as mentioned previously. By employing a mixed design with between- subjects test variables, the present study avoided those pitfalls, thereby enabling the

collection of data from a larger sample with a lower attrition rate and fewer confounds

due to repeated testing.

The benefits and strengths of employing a dietary manipulation to investigate the

effects of tryptophan manipulation on neuropsychological performance will help elucidate the role played by tryptophan on cognitive functioning.

Method

Participants

Participants were recruited in two ways. The primary method involved recruiting

undergraduate students enrolled in a psychology course at the University of Windsor who

had signed up for the online participant pool. These students received course credit in

exchange for taking part in this study. A list of students who had signed up for the pool

and who met our criteria for Body Mass Index (BMI) range (greater than 18.5, the lower

cut-off for ‘underweight’, and less than 29.9, the upper cut-off for ‘overweight’) was emailed to the researcher. Those students were then sent an email advertisement for the study (see Appendix B for Study advertisement). This advertisement explained that in Tryptophan 53 order to take part in the testing session, participants must first complete an in-person screening interview, after which time they may elect to sign up for the testing session if they are eligible to do so. The screening session of the study was worth a total of 0.5 course credits and the testing session was worth a maximum of 5.5 bonus points, provided the participant completed the entire session. Those who were interested contacted the researcher and an appointment was set up to take part in the screener (see

Appendix C for study screener). The secondary method of recruitment was comprised of posters which were placed throughout the campus community inviting students from other faculties to take part in the screener, with the option of signing up for the study should they be eligible (see Appendix D for poster advertisement). Those who were interested in taking part contacted the researcher and in return were sent the email advertisement of the study. If upon reading the email advertisement they were still interested in participating, an appointment was made to take part in the screening session.

Of note, these participants were not eligible to earn bonus points towards their course(s).

Thus, this was a two-part study consisting of a screening session (lasting approximately half an hour) and a testing session (lasting approximately 5.5 hours). All participants who signed up for and successfully completed the testing session, regardless of the recruitment method, were given the option of having their name entered into a draw to win 1 of 2 gift cards each valued at $50 CAD to either Devonshire Mall or Future Shop

(the winners had the option of choosing their reward). Ethics approval was gained by the

University of Windsor Research Ethics Board and informed consent was obtained from all participants before completing both the screener and the testing session (see Appendix

E for the test screener consent form and Appendix F for the testing session consent form). Tryptophan 54

A total of 103 participants were screened for inclusion in this study, of which 82 were eligible to take part in the testing session. Of those deemed eligible, 73 participants successfully completed the testing session. Participants were split across conditions in the following manner: 25 in the Augmented group (17 female, 8 male), 25 in the

Balanced group (17 female, 8 male), and 23 in the Depleted group (16 female, 7 male)

(see Procedures for details on group assignment). All participants in this study regularly ate breakfast and lunch, were not colour blind, and had no motor problems. None of the females were pregnant or lactating. Complete demographic information for each group can been seen in Table 2.

Design

This study employed a double-blind, mixed design. Pre- and post-test measures of working memory (the Digit Span – backward trial) and affect (PANAS; Watson, Clark

& Tellegen, 1988) served as within-subject variables to assess the success of the tryptophan manipulation (depletion, augmentation or balanced). All other test measures were between-subject variables. A maximum of 30 days separated the screening and testing sessions.

Procedures

Screening Session. All participants who signed up for the screen came into the laboratory and, after signing an informed consent form, completed an initial screening interview with the author (see Appendix C). During this interview, participants were assessed for suitability for inclusion in the study according to the following criteria: absence of food allergies (especially peanuts); confirmation of a body mass index (BMI) Tryptophan 55

Table 2

Demographic Information for Each Condition

Variable Augmented Balanced Depleted

(N = 25) (N = 25) (N = 23)

Age M (SD) 21.6 (3.1) 22.6 (3.38) 21.3 (2.51)

Females 21.4 (2.92) 22.5 (3.13) 20.6 (2.00)

Males 22.1 (3.72) 22.9 (4.09) 23.0 (2.89)

Gender N (%)

Female 17 (68) 17 (68) 16 (69.6)

Male 8 (32) 8 (32) 7 (30.4)

Screeners N 103

Ineligible 17

Declined Test Session 3

No Show 1

Completed/Eligible 82

Testers N 82

No Shows 3

Cancellations 4

Administration Errors 2

Final Sample 73

ESL N (%)

Yes 7 (28) 9 (36) 8 (34.8)

No 18 (72) 16 (64) 15 (65.2) Tryptophan 56

Education M (SD) 15.0 (2.5) 15.4 (2.36) 15.11 (2.22)

Female 14.9 (2.64) 15.7 (2.40) 14.4 (1.89)

Male 15.3 (2.31) 14.69 (2.27) 16.6 (2.29)

BMI M (SD) 22.4 (2.57) 22.56 (2.88) 22.70 (3.02)

Female 22.0 (2.48) 22.0 (2.95) 21.8 (2.69)

Male 23.4 (2.64) 23.75 (2.48) 24.6 (2.98)

Weight (lbs) M (SD)

Female 126.7 (13.9) 136.88 (17.5) 131.56 (14.00)

Male 167.4 (28.9) 165.88 (21.4) 167.29 (11.69)

Physical Activity Level (weekly) N

Female

Not at all 1 1 0

Minimal (walking to school) 12 8 1

Quite (3-5 times/week) 4 6 14

Very (6+ times/week) 0 2 1

Male

Not at all 0 0 0

Minimal (walking to school) 2 5 1

Quite (3-5 times/week) 5 2 5

Very (6+ times/week) 1 1 1

Frequency of Food Consumption N

Female

Fast (0-2 hours) 5 2 4 Tryptophan 57

Average (3-5 hours) 11 14 12

Slow (6+ hours) 1 1 0

Male

Fast (0-2 hours) 2 0 1

Average (3-5 hours) 4 6 5

Slow (6+ hours) 2 2 1

Beck Depression Inventory – II

(BDI - II) Score M (SD)

Female 3.24 (4.06) 6.12 (5.12) 4.63 (3.48)

Male 5.38 (4.31) 5.00 (4.66) 8.14 (4.67)

History of Depression N

Female 1 0 0

Male 0 0 0

History of Anxiety N

Female 0 0 0

Male 0 0 0

Family History of Depression N

Female 6 4 2

Male 2 1 0

Smoker N

Female 1 1 0

Male 1 1 2

Birth control use (female) N 10 5 8 Tryptophan 58

Hours of sleep/night M (SD)

Female 6.88 (1.38) 7.79 (1.03) 7.50 (1.26)

Male 7.06 (1.05) 7.56 (1.08) 6.86 (1.11)

Amount of caffeine (daily) N

Female

Low (0-1 drinks/day) 13 14 14

Medium (2-3 drinks/day) 4 2 2

High (4 drinks/day) 0 1 0

Male

Low (0-1 drinks/day) 5 5 4

Medium (2-3 drinks/day) 2 2 3

High (4 drinks/day) 1 1 0

Tryptophan 59

between the values of 18.5 and 29.9; absence of chronic or current physical illness,

including gastrointestinal disorders such as Crohn’s disease, irritable bowel syndrome, or

lactose intolerance as these conditions have been shown to impede absorption of nutrients

(Murray, 1998); no neurological, endocrine or metabolic disorders; no current medication

use (including SSRIs, MAOIs, narcotics, anti-psychotics, anxiolytics, or stimulants); no

irregular diets (i.e., no ‘fad’ diets or skipping meals) or eating disorders; and no current

episode of acute anxiety or depression. The Beck Depression Inventory – II (BDI-II;

Beck, Steer, & Brown, 1996) was administered to measure current levels of depression.

If a participant had a BDI score of 30 or greater (indicating severe depression), follow-up questions were asked as to the nature and severity of symptoms, including the likelihood of them hurting themselves or others. Any participant who scored in this range would

have been provided with appropriate referrals to the Windsor Regional Hospital Mood

and Anxiety Clinic, the Windsor Mood Disorders Self-Help Group, or the Student

Counseling Centre on campus; this information was also listed on the consent forms, of

which participants kept a copy. If anyone was currently suicidal or thinking about committing suicide, they would have been referred to the Community Crisis Centre (there is a telephone in the laboratory available for such use). Of note, no participant obtained a

score of 30 or greater, and as a precaution, the author pointed out the referral information

to any participant who obtained a score of 10 or greater. Furthermore, suicidal ideation

was not endorsed by any participant. History of anxiety or depression, family history of

mental illness, and diagnoses of diabetes were also documented, as was the typical

amount of caffeine, alcohol and tobacco consumed daily, and the average number of

hours of sleep per night. Information was also obtained about the participant’s level of Tryptophan 60 physical activity, frequency of food consumption, type and frequency of food cravings, and use of oral birth control (for women).

At this point, if a participant was deemed eligible to continue after the screen, the participant was given the option of signing up for the testing session. To take part in the testing session, participants must have agreed to fast 12 hours prior to initiation of testing.

They were informed that on the day of testing, they would be provided with breakfast, lunch and two snacks. They were also informed that the session would begin at 9 am and would last approximately 5 hours, although the actual testing would only take place during the last 1.5 hours of this 5 hour period. Participants were told that in the time between breakfast and the commencement of testing, they would be required to remain in the common waiting room (they were allowed to study, read, listen to music, and/or entertain themselves with their laptops; sleeping was not allowed). Lastly, participants were shown a list of foods they may be asked to eat when they come in to take part in the study (this allowed for the screening and confirmation of food allergies and/or sensitivities). If the participant agreed to these conditions, an appointment was made for the participant to come back another day to take part in the study. Each participant was instructed to abstain from alcohol consumption the day before testing, and to get a good night’s sleep (ranging from 7-10 hours, or whatever is considered average for each particular person) the night prior to coming in. Every effort was made to accommodate the participant’s school schedule (i.e., essay due dates and exams) when booking the testing session. Each participant thus came to the laboratory once for a screening session and once for the testing session. The author was responsible for conducting the screening sessions with participants, as well as for the quasi-randomization of participants into each Tryptophan 61

of the three meal conditions (augmented, balanced, or depleted tryptophan), matched for

BMI and gender. In order to achieve quasi-randomization, BMI scores were split into

lower (18.5-21.5), middle (22-25.5) and higher (26-29.9) scores for both males and

females, with the aim of recruiting an equal number of males and females from each

range of scores. In other words, the aim was to obtain an equal number of lower-male,

lower-female, middle-male, middle -female, higher-male and higher-female participants

for inclusion in this study. For example, if the first participant was a middle-male, he

might randomly have been assigned to the Augmentation condition. Thus, the next

middle-male would have been randomly assigned to either the Depletion or the Balanced

condition. The third middle-male will thus be assigned to whichever condition is still

empty for that gender and BMI range. The same process was repeated for female

participants. Within each gender, an equal number of participants from each BMI range

were assigned to each meal condition. As condition assignment was completed by the

author and not by the research assistants who administered the neuropsychological test

battery, the maintenance of a double-blind research design was thus ensured. A total of

103 participants were screened for this study, 82 of whom met eligibility criteria for

inclusion in the testing session.

The meals for each participant were put together the night before each testing day

by the author and labeled according to a master menu key (known only to the author),

thereby ensuring that the research assistants administering the test battery were blind to

the condition to which participants had been assigned. On the day of testing, the author

provided participants with their meals and snacks, as well as with fresh copies of the

PANAS at the designated times. The author was also responsible for ensuring that Tryptophan 62

participants completed their entire meal, and for removing all food trash from the waiting

room (to ensure that the research assistants could not inadvertently deduce to which

condition participants were assigned). The author informed participants that they were

not to divulge any information to the research assistant with whom they were paired

regarding the foods that were consumed. Participants were run either one or two at a

time, depending on recruitment and availability of the research assistants. Although each

participant worked with a separate research assistant once the testing started at 12:30 pm,

participants were together in the common waiting room during the time between

breakfast and the commencement of the testing (i.e., from 9 am until 12:30 pm). The

author was responsible for checking in with participants during this wait period. A total

of three research assistants were utilized in this study.

Testing Session. On the testing day, participants arrived at the laboratory by 8:45

am. Once they had signed the informed consent, they were quickly surveyed to ensure

they had met with the previously discussed pre-conditions for taking part in the test

session (namely: fasted for 12 hours, avoidance of alcohol and drugs the previous day, a

minimum of 6 hours sleep and no caffeine since the previous day). This brief screen was

conducted with each participant, one-on-one, by the author (on days when two

participants were being run concurrently, a research assistant would conduct this brief

screen with one of the participants). Upon confirmation that these conditions were met,

the participant was administered a brief measure of attention (the Digit Span) and was then brought into the waiting room. Once in the waiting room, the participant filled out the first PANAS while their breakfast was prepared and served at 9 am. Immediately after breakfast and again after the first snack, which is provided at 10:15 am, each Tryptophan 63 participant filled out a PANAS. Lunch was provided at 11 am, after which the PANAS was completed for a fourth time. Given that research has shown that several hours are required for plasma and free tryptophan levels to reach peak depletion (e.g., Benkelfat et al., 1994), all participants completed the neuropsychological battery at 12:30 pm, 1.5 hours after the provision of lunch (3.5 hours after the first meal was consumed). This is in line with Markus’s methodology. The fifth PANAS was completed just prior to the administration of the test battery. The test battery took less than 1.5 hours to complete, after which time participants completed the sixth and final PANAS, followed by the second and final administration of the Digit Span. Taken together, the PANAS and the

Digit Span (backward condition) served as within-subject indicators of the effectiveness of the tryptophan manipulation, enabling pre- and post-test comparisons in affect and cognitive performance. At this point, all participants were provided with the option of a final snack to replete tryptophan levels and to help offset any possible reactions to tryptophan augmentation or depletion (see Table 3 for schedule of events). Water was available ad libitum. Of the 82 participants deemed eligible to take part in this study, 3 failed to show up on the day of testing, 4 cancelled their testing session, and 2 administration errors resulted in a total of 73 participants successfully completing the testing session. Participants were split across conditions in the following manner: 25 in the Augmented group (17 female, 8 male), 25 in the Balanced group (17 female, 8 male), and 23 in the Depleted group (16 female, 7 male). Tryptophan 64

Table 3

Schedule of Events

Time Activity Administered by

8:45 am Arrive at lab, consent, pre-screen Author

8:50 am Complete pre-test Author

8:55 am Complete PANAS Author

9:00 am Breakfast is served Author

9:20 am PANAS is completed Author

10:15 am Snack is served Author

10:30 am PANAS is completed Author

11:00 am Lunch is served Author

11:20 am PANAS is completed Author

12:25 pm PANAS is completed Author

12:30 pm Neuropsychological test battery begins RA

2:00 pm Final PANAS is completed once Author

neuropsychological test battery has finished

2:05 pm Final snack is served Author

Tryptophan 65

Dietary Manipulations

The meals created for each of the three conditions were modeled after the diets provided by Markus and colleagues (1998) (see Appendix G for composition of meals and snacks). As Markus’s group did not provide the exact amount of each food provided to participants, instead citing only the total amount of carbohydrates, protein, fat and calorie intake in each meal, all meals for this study were created and analyzed by the author using the NutritionData website (NutritionData, 2009). This website enables the user to input the amount and type of food and creates a recipe label listing the total grams of carbohydrates, protein, fat, calories, and other nutritional facts about the foods contained therein. In this way, it was possible to replicate the menus created by Markus’s group so as to obtain the same carbohydrate:protein ratios (see Table 4 for macronutrient content of each condition). Thus, the ratios employed in the present study are in keeping with those employed by Markus such that the augmentation meal in the present study contained 18.2 times more carbohydrates than proteins, and the depletion meal in the present study contained 1.47 times more carbohydrates than proteins. As Markus’ group did not employ a balanced meal, the balanced meal in the present study was devised to have a carbohydrate:protein ratio between those used in the augmentation and depletion meals. Thus, the balanced meal has 8.37 times more carbohydrates than proteins. The final snack, composed of a pineapple cup and a yogurt cup, was chosen as these foods are known natural sources of tryptophan (Murray, 1998; Schmitt et al., 2000). Tryptophan 66

Table 4

Macronutrient Content of Each Condition

Meal Type Augmented Depleted Balanced

Carbohydrates Total grams 200 57 174 % of meal 67 19 58 % RDA 67 19 58

Protein Total grams 11 39 21 % of meal 15 45 2 % RDA 22 78 42

Fat Total grams 11 23 26 % of meal 18 36 40 % RDA 17 35 0.4

Calories Total grams 931 881 988

Note: Macronutrient content of these meals based on a 2,000 calorie diet. The Recommended Daily Allowance (RDA) for each macronutrient, based on a 2,000 calorie diet for males and females aged 4 and over as indicated by the Canada Food Inspection Agency (“Chapter 6”, n.d.), is as follows: Carbohydrates = 300 g; Protein = 50 g; Fat = 65 g. All meals were modeled after those used by Markus and colleagues (1998) and were created and analyzed using the NutritionData website (NutritionData, 2009). Tryptophan 67

Neuropsychological tests administered

The following is a list of the neuropsychological test measures that were utilized in this study, organized by test domain. A brief description of each test is provided, along with the scoring criteria that were employed. The interested reader is directed to

Lezak et al., (2004) for further detail regarding these measures.

Executive Functioning

Verbal Fluency (‘F’, ‘A’, ‘S’ + Animals; Benton, 1968)

The FAS is a measure of verbal fluency that assesses language generation and executive functions. Participants were instructed to list as many different words as possible in one minute that start with a specific letter while abiding by the following rules: no names or proper nouns (e.g., Brenda or Baltimore), no numbers, and no variants of a word (e.g., bank, banks, banked). For each of the three letters, participants were allotted one minute to respond. The total score was the total number of correct words

(i.e., non-perseverative words that did not break any of the rules) for all three letters, combined into a single score. On the semantic fluency task, participants were instructed to name as many different animals as they could in one minute (e.g., mammals, reptiles, birds, insects, etc.). The total score on the semantic trial was the total number of real animals produced in one minute that were not perseverative. In both the phonemic and semantic conditions, rule breaks were coded as responses that were a number, a name or proper noun, or that constituted a variation of a previously stated word (e.g., paint, paints); perseverative responses were coded when a word was repeated more than once.

Test-retest reliability for the FAS is quite high, over r = .70 for both the phonemic and the semantic trials (Basso, Bornstein, & Lang, 1999; Harrison, Buxton, Husain, & Wise, Tryptophan 68

2000). With regards to validity, the FAS is highly correlated with other measures of verbal fluency (e.g., the Controlled Oral Word Association Task, which uses the letters

‘C’, ‘F’, ‘L’), ranging from .85 to .94 across varying populations and settings, including healthy controls (M. J. Cohen & Stanczak, 2000; Lacy, Gore, Pliskin & Henry, 1996).

Stroop Color-Word Test (SCWT; Golden, 1978; Stroop, 1935)

Although it is often utilized as a measure of selective attention, the Stroop is considered a measure of cognitive control as it requires the inhibition of pre-potent (i.e., automatic) responses, forcing participants to ignore task-irrelevant stimuli. The version of the Stroop employed in this study (Golden, 1978) consisted of three separate trials:

word reading (black ink); colour naming (red, blue and green ‘X’s), and the colour-word

reading interference task (e.g., the word “red” written in blue ink). On this latter task,

participants were required to ignore the typed word and to name the colour of the ink in

which the words were typed. Participants were allotted 45 seconds for each of the three trials. Scores were calculated for each individual trial, producing a Word Score, a Color

Score and a Color-Word Score. An overall interference score was also derived by subtracting the participant’s age and education predicted color-word score from the actual color-word score achieve by the participant. The interference score indicates the degree to which participants are able to inhibit pre-potent responses. Test-retest reliability has been reported at r = .86 for the Word trial, at r = .82 for the Color trial, and at r = .73 for the Color-Word trial (Golden, 1975). Chafetz and Matthew (2004) report moderate to high validity, and there is a moderate correlation between the Interference score and other measures of prepotent response inhibition (e.g., time of the stop-signal task, r = .56; May Tryptophan 69

& Hasher, 1998) and attention (r = .31 with errors of omission on continuous

performance tasks; Weinstein, Silverstein, Nader & Turnbull, 1999).

Emotional Stroop (paper-and-pencil)

The emotional Stroop employed in this study followed the same principles as the

Stroop Color Word Test, with the exception that the words listed in the latter two trials were emotionally salient. Modeled after the 1978 Golden version of the Stroop, four trials were administered: reading of neutral words (e.g., hat, swim, book); colour naming of neutral words; colour naming of negative words (e.g., disaster, failure, pathetic); and colour naming of positive words (e.g., happy, smile, clean). Each trial contained 100 words. For the latter three trials, participants were required to name the colour of the ink in which the words were printed. A total of 45 seconds was allotted for each trial. Scores were calculated for each individual trial, producing a Word Score, a Color Score and a

Color-Positive Word Score, and a Color-Negative Word Score. An overall total interference score was also derived by subtracting the participant’s combined score for the Positive and the Negative Word Scores from the combined Word and Color Score.

In creating the emotional Stroop test used in this study, a review of the literature provided information pertaining to the appropriate word parameters to employ. Larsen,

Mercer, and Balota (2006) analyzed the lexical characteristics of words used in emotional stroop experiments. From the studies they analyzed that utilized negative, positive, and neutral conditions, we chose to use the neutral and positive word lists from Compton,

Heller, Banich, Palmieri, and Miller (2000). Since these lists contained 12 words, we eliminated two words in order to fit our format (i.e., 10 positive, 10 negative and 10 neutral words). Since the negative word list from Compton’s study included words of a Tryptophan 70

threatening nature, as opposed to a purely negative emotional nature, we created our own

negative word list by utilizing the online MRC Psycholinguistic Database

(http://www.psy.uwa.edu.au/mrcdatabase/uwa_mrc.htm) (Coltheart, 1981). We limited

our word search to match the lists employed by Compton and Larsen’s groups in terms of

word length, number of syllables, concreteness, imageability, and familiarity. All words

were one syllable and 3-6 letters long. The concreteness, imageability, and familiarity

ratings for the positive word list used in Compton’s study were 359, 435, and 609,

respectively, whereas the ratings for the neutral word list were 373, 442, and 624,

respectively. Limits in the Psycholinguistic database were set at 100 higher and lower than these ratings. The concreteness, imageability, and familiarity ratings for the negative word list created for this study were 358, 436, and 540, respectively. These ratings were similar to those of the neutral and positive lists used by Compton’s group.

Attention/Concentration

Digit Span (DS; from the Wechsler Adult Intelligence Scale –Third Edition (WAIS-III);

Wechsler, 1997)

The Digit Span is a measure of auditory attention span and working memory. In

this task, participants were required to listen to and repeat an aurally presented string of

numbers that increased in length with each successive trial. The task was discontinued

following errors on both digit strings within a trial. The task was then completed in a

backward condition wherein participants were required to repeat a string of aurally

presented numbers backwards (i.e., in the reverse sequence as was presented). The

backwards condition, which taps into the domain of working memory, is thus the harder

of the two conditions. Discontinuation on the backward condition occurred when both Tryptophan 71

digit strings within a trial were incorrect. The total number of digits correctly recalled in

both the forward and the backwards trials were calculated by simple summation of

correct responses, resulting in a total forward score, a total backward score, and an

overall total score. Scores range from 0-16 on the forward condition, and from 0-14 on

the backward condition. Scores on the backward condition were employed as pre- and

post-test measures of the tryptophan manipulation as there is evidence in the literature

that this task is sensitive enough to differentiate between tryptophan augmentation and

deletion (e.g., Luciana et al., 2001). The reliability of the Digit Span subset is high (r =

.90). Digit Span correlates the best with the Letter-Number Sequencing subtest from the

WAIS-III (r = .57), and demonstrates a moderate correlation with the Verbal Scale (r =

.51) (Sattler, 2001).

Letter-Number Sequencing (from WAIS-III; Wechsler, 1997)

Letter-number Sequencing is a measure of working memory and attention that

involves the aural presentation of complex auditory material (letters and numbers) that

the participant must mentally manipulate and reproduce according to specific criteria

(i.e., letters in alphabetical order, followed by numbers in numerical order). There is no

time limit on this task, and discontinuation occurred when all three trials of an item are

incorrect. The total number of correct trials was calculated. The reliability of the Letter-

Number Sequencing subtest is high (r = .82), demonstrating a moderate correlation with the Verbal Scale of the WAIS-III (r = .62). Of the other subtests comprising the WAIS-

III, Letter-Number Sequencing best correlates with Digit Span (r = .57) (Sattler, 2001).

Tryptophan 72

Digit Symbol – Coding (from WAIS-III; Wechsler, 1997)

Digit Symbol – Coding is a task of visual attention and working memory. In this task, participants were required to re-code a series of symbols using the key-code provided at the top of the page. This is a timed task, and discontinuation occurred after two minutes had lapsed. The total number of correctly recoded symbols served as the score for this task. The Digit Symbol – Coding subtest of the WAIS-III is reliable (r =

.84) and demonstrates a moderate correlation with the Performance Scale (r = .50)

(Sattler, 2001).

Ruff 2 & 7 Selective Attention Test (Ruff & Allen, 1996)

The Ruff 2 and 7 Selective Attention Test is a selective visual cancellation task that assesses the difference between automatic and controlled visual search (i.e., processing speed). In this task, participants were presented with 20 blocks of stimuli, each of which consisted of either three rows of letters (automatic search) or three rows of numbers (controlled search). Participants were instructed to cross off (with a pen) all of the 2’s and 7’s that they could within a 15 second block of time. At the end of each 15 second period of time, participants were instructed to stop and to continue with the next block of stimuli. This task takes a total of 5 minutes to complete and is scored according to both speed and accuracy of automatic and controlled search. Thus, for the letter trials, the following scores were derived: Automatic Detection Speed (i.e., total number of correct hits), Automatic Detection Errors (i.e., the total number of errors) and Automatic

Detection Accuracy scores (calculated in the following manner: Automatic Detection

Speed divided by the sum of the Automatic Detection Speed score plus the Automatic

Detection Errors score, multiplied by one hundred). For the digit trials, scores were Tryptophan 73 derived for Controlled Search Speed (i.e., total number of correct hits), Controlled Search

Errors (i.e., the total number of errors), and Controlled Search Accuracy (i.e., Controlled

Speed score divided by the sum of Controlled Search Speed score plus Controlled Search

Errors, multiplied by one hundred). Total Speed and Total Accuracy scores, as well as

Speed Differences, Accuracy Differences, and Total Difference were also calculated by adding or subtracting speed and accuracy scores, respectively. Ruff and Allen (1996) report that Speed scores yield higher test-retest reliability than do Accuracy scores;

Lemay, Bedard, Rouleau, and Tremblay (2004) found a .85 correlation between Speed scores. Although content validity is mainly based on theoretical grounds (Strauss,

Sherman, and Spreen, 2006), it has been reported that Digit Symbol, which also assesses processing speed, is the test most highly correlated with the Ruff 2 & 7 (r = .35-.40) and in normal samples it is not correlated with other tests designed to measure attention (e.g.,

Digit Span, Stroop; Ruff & Allen, 1996).

Trail Making Test (Trails A & B; Reitan, 1958)

The Trail Making Test is a speeded visual attention task involving simple sequencing of numbers. On the first trial (Trails A), participants were instructed to connect the numbers on the page as quickly as they could without taking their pen off of the page. The second trial (Trails B) was essentially the same task save for the fact that it entails alternating between letters and numbers, making it the more complex of the two tasks. This is a timed test requiring participants to connect the circles of letters (or letters and numbers) as quickly as possible. The total time required for each condition served as the score on each trial. Dikmen, Heaton, Grant, and Temkin (1999) report reliability for both Trails A (.79) and Trails B (.89) as adequate to high, respectively. There is a modest Tryptophan 74

correlation between Trails A and B (r = .31-6), a range that is thought to reflect the

greater cognitive demand of the latter as opposed to the former trial (Heilbronner, Henry,

Buck, Adams, & Fogle, 1991).

Memory

California Verbal Learning Test - II (CVLT-II; Delis, Kramer, Kaplan, & Ober, 2000)

The CVLT-II is an aurally presented list learning task requiring the participant to

learn and recall verbal information immediately after presentation. There are five

learning trials, in which the list is repeated each time after which the participant must

reproduce as many words from the list as possible. An interference trial was

administered, followed by Short-Delay Free Recall and Short-Delay Cued Recall trials.

After a 20 minute delay, Long-Delay Free Recall, Long-Delay Cued Recall, and Long-

Delay Recognition trials were administered. Thus, scores were calculated for: Trials 1-5

Recall Total Correct; List B Free Recall Correct; Short-Delay Free Recall; Short-Delay

Cued Recall; Long-Delay Free Recall; Long-Delay Cued Recall; Free Recall Intrusions;

Cued-Recall Intrusions; Total Intrusions; Total Repetitions; Long-Delay Recognition;

Long-Delay Recognition False Positives; and Long-Delay Forced Choice Recognition

Accuracy. According to the test manual, reliability is high (r = .80-.89) for Trials 1-5

Recall Total Correct, Short- and Long-Delayed Free Recall, and Total Recognition. The test manual also reports validity scores ranging from .60-.69 for Free-Recall Intrusions to

.80-.89 for Long-Delayed Recognition False Positives.

Tryptophan 75

Rey-Osterrieth Complex Figure Test (R-OCFT; Rey, 1941; Osterrieth, 1944)

The R-OCFT measures a participant’s ability to accurately copy a complex figure

onto a sheet of paper. Successful completion requires that participants be able to

accurately perceive and synthesize the numerous components of the figure. After the

copy trial, immediate (3 minute delay) and delayed (25-35 minute delay) recall trials

were administered to assess the integration, memory and synthesis of the figure.

Participants also completed a recognition trial to help determine whether performance

was affected by difficulties with perception, synthesis, or retrieval of complex visual

information. Thus, scores were calculated for Immediate Recall, Delayed Recall,

Recognition Total Correct, Copy, and Time to Copy, as well as for Recognition True

Positives, Recognition False Positives, Recognition True Negatives and Recognition

False Negatives. Meyers and Meyers (1995) report reliability scores of r = .76 for

Immediate Recall, of r = .89 for Delayed Recall, and of r = .87 for Recognition Total

Correct. According to Strauss and colleagues (2006), the R-OCFT is a valid measure of

visual-construction (via the copy trial) and memory (recall and recognition trials).

Mood/Affect

Positive and Negative Affect Scale (PANAS; Watson, Clark, & Tellegen, 1988)

The PANAS is a self-report inventory comprised of both a negative affect and a

positive affect subscale. Each scale consists of 10 items, and participants were required

to rate (on a 5-point scale) how well each descriptor described them at that particular

moment. Examples of negative descriptors are irritable, distressed, guilty, or scared;

positive descriptors include such items as determined, strong, enthusiastic, or proud.

Watson (1988) reported correlations of between -. 12 to -.26 for the PANAS scales, Tryptophan 76

indicating that the negative affect and the positive affect scales are independent of one

another. With regards to validity, Watson (1988) stated that “[a]ll of the scales are

reasonably convergent with other measures of the same factor, and one must conclude

[that the NA and PA] scales have comparable correlates and lead to similar conclusions”

(p. 138). Discriminant validity between the NA and PA scales has also been reported,

with correlations in the range of r = -.48 (Warr, et al., 1983) to r = .54 (Watson, 1988).

Beck Depression Inventory-II (BDI-II; Beck, Steer, & Brown, 1996)

The BDI-II is a self-report inventory consisting of 21 items, each of which is

scored on a four-point scale. Indecisiveness, Mood, and Sense of Failure are examples of

items on the scale, each of which pertains to a particular symptom of depression. The

scores for each item were summed together to arrive at a total score; lower scores

translate into lesser degrees of depression. A score of 30 or greater indicates severe

depression. If a participant scored in this range, follow up questions were asked by the

researcher as to the nature and severity of symptoms, including the likelihood of the

participant hurting him or herself or others. No participants scored in this range. As a

precaution, all participants who scored 10 or above were provided with referrals to the

appropriate services, all of which have their contact information listed on the consent

form signed by the participant. If anyone had of endorsed the suicide item, they would have been walked over to the Student Counseling Centre at the CAW by the researcher.

No one endorsed this item. The BDI-II was only administered as part of the screening procedures in order to ensure no current depression; it was not administered during the testing session.

Tryptophan 77

Results

Prior to analyses, all variables were examined for accuracy of data, missing values, normality and outliers. Of the 73 participants who completed this study, five participants failed to complete one of the six PANAS forms and thus these participants with missing data were excluded from analyses relevant to the PANAS; all other analyses contained data from all 73 participants. Data was screened for multivariate outliers using

Mahalanobis’s distances, and none were found. All assumptions of analyses of variance

(ANOVA), multivariate analyses of variance (MANOVA) and repeated measures were met (or corrected for). Raw test scores were used in all analyses, and data was analyzed using SPSS for Windows Version 17 (SPSS Inc., Chicago, IL, USA).

A correlation matrix was conducted in order to examine the relationship between the background variables (e.g., age, education, physical activity level, BDI score, etc.) and all cognitive and affective measures. Results of this analysis can be seen in Table 5.

As can be seen from Table 5, several key measures did not correlate with any background variables (e.g., CVLT Long Delay Recall, Rey-O Delayed Recall); every background variable correlated with at least one test measure.

As we were unable to recruit equivalent numbers of males and females, it was unclear whether there were any gender differences on the background variables of English as a

Second Language (ESL), eating frequency1, level of physical activity2 or BMI. This was an important consideration as many researchers within the field have collected data only

1 ‘Eating frequency’ is the term used in this document to refer to the average number of hours between eating each meal or snack as reported by the participant during the screening session. 2 Levels of physical activity was measured via self-report by each participant during the screener. A 4- point Likert scale was utilized, enabling participants to report their levels of physical activity during a typical week as either “Not at all” (i.e., no exercise of any kind), “Minimal” (e.g., walking to school), “Quite” (physical activity 3-5 times per week), or “Very” (physical activity 6 or more times during the week). See Appendix C for more detail. Tryptophan 78

Table 5

Correlations Between Background Variables and Tests Comprising Predictions and Composite Scores a.

Test Age Educb. BMIc Weight Height Eating Sleep BDIe Physical (lbs) (in.) Freq.d (hrs) Activity f

1. CVLT-II g Long Delay Recall .22 .28 .18 .12 -.03 -.10 -.09 -.17 -.04

2. Rey-O Delayed Recall .12 .20 .21 .10 -.07 .18 -.16 -.03 -.22

3. Stroop Interference .09 .09 -.14 -.11 .01 -.06 .10 .00 -.20

4. Trails A -.25* -.20 -.28* -.33** -.19 .16 .25* -.05 .16

5. Trails B -.13 -.06 -.10 -.20 -.16 .07 .14 .07 .13

6. Ruff 2 & 7 Total Speed .25* .29* .22 .31** .23 -.05 -.02 .02 -.20

7. Ruff 2 & 7 Total Accuracy .12 .15 -.24 -.05 .14 -.12 -.08 -.11 -.40

8. Digit Symbol Coding .01 .09 -.07 -.08 -.00 -.32** .15 -.15 -.14

9. Letter Number Sequencing .01 -.04 -.02 .09 .14 -.23 .00 -.09 -.25

10. EStroop Positive Interference -.08 -.10 -.08 -.02 .07 -.24* .15 .08 -.10

11. EStroop Negative Interference -.06 .04 -.08 -.22 -.21 -.35** -.10 -.21 -.12

12. Digit Span 2 Total .30* .24* .05 .13 .11 -.02 .07 -.26* -.34

Tryptophan 79

Test Age Educb. BMIc Weight Height Eating Sleep BDIe Physical (lbs) (in.) Freq.d (hrs) Activity f

13. FAS h Total .33** .20 .17 .05 -.05 .05 .05 -.17 -.16

14. Working Memory .27* .17 .08 .17 .13 -.13 .05 -.22 -.32

15. Attention .11 .16 -.18 -.06 .09 -.17 .16 -.17 -.34

16. Positive PANAS i 1 .20 .13 .03 .13 .16 .20 -.22 .04 .13

17. Positive PANAS 2 .08 .04 .03 .10 .11 .13 -.24 .05 .07

18. Positive PANAS 3 -.02 -.04 .01 .15 .20 .07 -.21 .10 .11

19. Positive PANAS 4 -.01 .00 -.11 .04 .15 .14 -.30* .11 .13

20. Positive PANAS 5 .04 .04 .01 .12 .16 .06 -.34** .16 .13

21. Positive PANAS 6 .04 .50 -.05 .08 .18 .01 -.24 .11 .17

22. Negative PANAS 1 -.14 -.18 .07 .12 .14 .02 -.13 .58** .20

23. Negative PANAS 2 -.09 -.12 .08 .06 .02 .09 -.09 .51** .10

24. Negative PANAS 3 -.15 -.17 .16 .08 -.04 .04 -.18 .58** .20

25. Negative PANAS 4 -.12 -.16 .07 .09 .07 -.03 .03 .58** .13

26. Negative PANAS 5 -.12 -.19 .11 .08 .02 -.04 -.05 .54** .15

Tryptophan 80

Test Age Educb. BMIc Weight Height Eating Sleep BDIe Physical (lbs) (in.) Freq.d (hrs) Activity f

27. Negative PANAS 6 -.08 -.11 .09 .08 .05 .04 -.01 .49** .06

** p < .01, * p < .05 a Collapsed across gender; b Education (years); c Body Mass Index; d Eating Frequency = average time (hrs) between each meal and/or snack; e Beck Depression Inventory - II score; f biserial correlation conducted on dichotomized (i.e., ‘low’ and ‘high’) variable; g California Verbal Learning Test-II; h ‘F’, ‘A’, ‘S’ verbal fluency test; i Positive And Negative Affect Scale. Note. All PANAS correlations excluded participants with missing data (n = 68). Tryptophan 81

on males (e.g., Fischer et al., 2002; Hughes et al. 2003; Lieberman et al., 2002; Park et al., 1994) or females (e.g., Nabb & Benton, 2006). Thus, examining each gender separately allowed us to better compare our findings to those in the literature.

Looking at each gender separately, ESL proportions did not differ for females

[χ²(2, N = 50) = .01, p =.994] or males [χ²(2, N = 23) = 1.10, p =.577]. With regards to

eating frequency, it had been suggested by Craig (1986) that the amount of time between each meal is likely to influence the effect of the manipulation on performance in that those with a faster metabolism may have a different peak level of augmentation or depletion than those with a slower metabolism. For this reason, a chi-square analysis was

also conducted on eating frequency, demonstrating no significant group differences for

either females [χ²(4, N = 50) = 2.60, p =.627] or males [χ²(4, N = 23) = 2.63, p =.622].

The chi-square analysis examining the proportions of physical activity levels across meal types for females, however, violated the assumption of expected frequencies, with more than 20% of the cells having an expected cell count of less than 5, thus rendering this analysis uninterpretable. Examination of the chi-square table illustrated that the lowest

(i.e., ‘Not at all’) and highest (i.e., ‘Very’) categories of physical activity for each meal condition were the cells with expected frequency counts of less than 5.

This analysis was repeated for the males, with the same result being obtained.

The assumption of expected frequencies was violated, as all nine cells had an expected cell count of less than 5, again rendering the analysis uninterpretable. Examination of cell counts in the chi-square table, it is evident that the lowest category (i.e., ‘Not at all’), which was not endorsed by any males, and the highest category (i.e., ‘Very’) of physical Tryptophan 82

activity for each meal condition were the cells that violated the assumption of expected

frequencies most gravely.

Since the values in the ‘Not at all’ and ‘Very’ categories for both the females and

the males rendered the analyses uninterpretable due to their low levels of endorsement,

we collapsed across these more extreme activity levels to instead create two categories of

physical activity. The ‘low’ category was generated by collapsing across the ‘Not at all’

and the ‘Minimal’ levels of activity, whereas the ‘high’ category was created by

collapsing across the ‘Quite’ and the ‘Very’ levels of activity. By doing so, the chi- square analysis of physical activity levels no longer violated the assumption of expected frequencies for females. Levels of physical activity (using these dichotomized ‘low’ and

‘high’ physical activity levels) were significantly disproportionate across meal conditions for females [χ²(2, N = 50) = 16.86, p =.000]. The Augmented group had a greater proportion of participants within the ‘low’ level of physical activity (n = 13, 76.5%), whereas the Depleted group had a greater proportion of participants within the ‘high’ category of physical activity (n = 15, 93.8%) (see Table 6).

A chi-square analysis examining levels of physical activity (using the dichotomized ‘low’ and ‘high’ physical activity levels) was also conducted for the males and demonstrated a violation of the assumption of expected frequencies. Since more than

20% of the cells had an expected cell count of less than 5, the analysis was uninterpretable (see Table 7). Tryptophan 83

Table 6

Chi-square Results for Proportion and Percent Total of Dichotomized Physical Activity

Levels by Meal Type for Females

Physical Activity Levels Low High Meal Count (%) Count (%)

Augmented 13 (76.5) 4 (23.5)

Depleted 1 (6.3) 15 (93.8)

Balanced 9 (52.9) 8 (47.1)

Tryptophan 84

Table 7

Chi-square Results for Proportion and Percent Total of Dichotomized Physical Activity

Levels by Meal Type for Males

Physical Activity Levels Low High Meal Count (%) Count (%)

Augmented 2 (25.0)* 6 (75.0)

Depleted 1 (14.3)* 6 (87.5)*

Balanced 5 (62.5)* 3 (37.5)

*expected cell count of less than 5. Tryptophan 85

When BMI was analyzed separately for each gender, no significant difference

emerged between meal types for either the females [F(2, 47) = .02, p =.985, partial η2=

.00] or the males [F(2, 20) = .43, p =.656, partial η2= .04] (see Table 8 for group means

and SDs).

Overall, no gender differences were found for ESL or eating frequency. Levels of

physical activity, although significant for the females when dichotomized into ‘low’ and

‘high’ levels of activity, was not significantly correlated with any of the variables on which the predictions were based. Thus, despite there being an unequal proportion of levels of physical activity among female participants in Augmented and Depleted conditions (respectively), it does not appear that this difference was great enough to influence test scores. For this reason, level of physical activity is excluded from all further analyses. For exploratory purposes, however, all female analyses were repeated, examining low- and high-activity level participants separately on each test measure. The results were largely the same. The only significant difference was on the EStroop

Positive Interference for the high-activity females [F(2, 24) = 3.84, p =.036, partial η2=

.24]. Post-hoc comparisons showed a significant difference between those in the

Augmented group (M = 12.00, SD = 4.24; n = 4) and those in the Depleted group (M =

2.80, SD = 7.04; n = 15). With regards to BMI, when taken together with the results of the correlation matrix and above mentioned ANOVA, results of these analyses indicate that the BMI distribution is equal between meal groups and the difference is thus not large enough to influence test scores. For this reason, BMI was excluded from further analyses. This is in keeping with the norm within the literature in that researchers may Tryptophan 86

Table 8

Mean and Standard Deviation of BMI Scores by Gender and Meal Type

BMI Score Female Male Meal Type M SD M SD

Augmented 21.97 2.48 23.38 2.64

Depleted 21.84 2.69 24.64 2.98

Balanced 22.00 2.95 23.75 2.48

Tryptophan 87

control for BMI when recruiting participants (e.g., Markus et al., 1998; Nabb & Benton,

2006), but they do not include it in subsequent analyses.

Effects of the Tryptophan Manipulation

Working memory and self-report affect indices have been found to be sensitive measures in previous studies examining the effects of tryptophan manipulation on neuropsychological performance (e.g., Kanarek & Swinney, 1990; Lieberman et al.,

2002; Luciana et al., 2001). For this reason, the Digit Span Backwards scores and the

PANAS NA and PA scores over time were employed to serve as indicators of the

effectiveness of the tryptophan manipulation. In order to assess whether the dietary

method of tryptophan manipulation successfully altered levels of circulating tryptophan

in females, a one-way ANCOVA of meal type (augmentation, depletion, or balanced)

was conducted on the Digit Span Backward Time 2 raw scores, with the Digit Span

Backward Time 1 raw score entered as a covariate. There was no main effect of meal

type [F(2, 46) = .61, p =.549, partial η2= .03]. As expected, however, Digit Span

Backward Time 1 score was a significant covariate [F(1, 46) = 24.54, p =.000, partial η2=

.35]. An identical analysis was conducted for the male participants. As with the females,

there was no main effect of meal type [F(2, 19) = .34, p =.713, partial η2= .04], but Digit

Span Backward Time 1 score was a significant covariate [F(1, 19) = 15.04, p =.001,

partial η2= .44]. These results indicate that there were no significant between group differences for either females or males on the Digit Span Backward Time 2 score, one of the two pre- post-test measures selected to examine the effectiveness of the manipulation

(see Table 9 for mean scores on Digit Span Backward 2 scores split by gender and meal type). Tryptophan 88

Table 9

Mean and Standard Deviation of Test Scores on Digit Span Backward 2 Scores by

Gender and Meal Type

Digit Span Backward 2 Scores Female Male Meal Type M SD M SD

Augmented 8.47 2.27 8.63 2.62

Depleted 8.19 2.51 8.71 2.56

Balanced 7.29 2.42 7.50 2.73

Tryptophan 89

In order to determine whether mood scores changed over time as a function of the

manipulation, a repeated measures ANOVA of meal type on the NA scale of the PANAS

(administrations 1 through 6) was conducted for each gender separately. For the females,

Mauchly’s test indicated that the assumption of sphericity had been violated for the main

effect of NA, χ²(14) = 60.28, p =.000. Thus, degrees of freedom were corrected using

Greenhouse-Geisser estimates of sphericity (ε = .65 for the main effect of NA). The

main effect of NA was not significant [F(3.24, 149.23) = 1.23, p =.301, partial η2= .03], nor was the main effect of meal type [F(2, 46) = .08, p =.923, partial η2= .00]. The

interaction between NA and meal type was also not significant [F(10, 230) = .42, p

=.936, partial η2= .02].

These analyses were repeated for the males. As with the females, Mauchly’s test

indicated that the assumption of sphericity had been violated for the main effect of NA,

χ²(14) = 54.57, p =.000. Thus, degrees of freedom were corrected using Greenhouse-

Geisser estimates of sphericity (ε = .50 for the main effect of NA). The main effect of

NA was not significant [F(2.52, 40.24) = 4.00, p =.019, partial η2= .20], nor was the main

effect of meal type [F(2, 16) = .51, p =.611, partial η2= .06]. The interaction between NA

and meal type was also not significant [F(10, 80) = 1.14, p =.343, partial η2= .12] (see

Table 10 for mean NA scale scores split by gender and condition).

An identical set of repeated measures ANOVAs were conducted examining the

effect of meal type on the PA scale of the PANAS (administrations 1 through 6) for each

gender. For the females, Mauchly’s test of sphericity indicated that the assumption of

sphericity had been violated for the main effect of PA, χ²(14) = 34.48, p =.002. Thus,

degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (ε = Tryptophan 90

Table 10

Mean and Standard Deviation of Test Scores on Negative Affect (NA) Scale by Gender and Meal Type

NA Scale Scores Female Male Meal Type M SD M SD

NA Scale 1

Augmented 12.69 4.25 14.17 5.91

Depleted 12.56 3.48 12.83 3.66

Balanced 12.47 4.35 15.57 4.04

NA Scale 2

Augmented 11.50 2.76 12.17 2.48

Depleted 12.44 4.46 12.17 3.25

Balanced 11.76 4.76 12.86 2.48

NA Scale 3

Augmented 12.38 3.14 12.67 3.08

Depleted 12.44 3.03 12.17 3.37

Balanced 11.71 2.95 12.86 1.95

NA Scale 4

Augmented 11.88 3.69 12.17 1.94

Depleted 12.13 2.47 11.83 2.56

Balanced 12.18 3.19 12.29 1.80

Tryptophan 91

NA Scale Scores Female Male Meal Type M SD M SD

NA Scale 5

Augmented 12.06 2.79 12.67 2.66

Depleted 12.00 2.16 11.50 1.52

Balanced 12.00 2.96 13.00 2.31

NA Scale 6

Augmented 12.19 4.02 12.33 2.34

Depleted 13.31 5.21 13.67 3.61

Balanced 12.47 2.18 16.57 6.90

Tryptophan 92

.76 for the main effect of PA). There was no significant main effect for PA [F(3.80,

174.93) = 1.69, p=.157, partial η2= .04]. The main effect of meal type was also not

significant [F(2, 46) = .59, p =.599, partial η2= .03]. There were no significant

interactions between PA and meal type [F(10, 230) = .17, p =.998, partial η2=.01].

These analyses were repeated for the males. As with the females, there was no

significant main effect for PA [F(5, 75) = .95, p =.455, partial η2= .06]. The main effect

of meal type was also not significant [F(2, 15) = .66, p =.530, partial η2= .08]. There was, however, a significant interaction between PA and meal type [F(10, 75) = 2.19, p

=.028, partial η2= .23]. Post-hoc comparisons indicate that there was a near-significant

difference between meal types on the fourth administration of the PA, t(15) = -2.13, r =

.48, with those in the Augmented group scoring lower than those in the Depleted group.

As this value is equal to the established p = .05 cut-point for a significant finding and is

only present on one of the six PANAS administrations, it is likely that this result is

spurious and not meaningful (see Table 11 for mean PA scale scores split by gender and

condition).

Overall, these analyses indicate that there were no significant between group

differences for males or for females on pre- and post-test affective scores as measured by

the PANAS NA and PA scales.

Hypothesis 1: Depletion will result in lower scores on measures of LTM.

An ANOVA was conducted examining the effect of meal type on the CVLT

Long-delay Free Recall scores for females. There was no significant main effect of meal

type on the total number of words recalled during the long-delay free recall [F(2, 47) =

.13, p =.882, partial η2=.01]. An identical analysis was conducted for the male Tryptophan 93

Table 11

Mean and Standard Deviation of Test Scores on Positive Affect (PA) Scale by Gender and Meal Type

PA Scale Scores Female Male Meal Type M SD M SD

PA Scale 1

Augmented 26.69 5.75 29.50 6.57

Depleted 23.75 6.95 31.00 6.60

Balanced 23.76 7.01 32.14 9.19

PA Scale 2

Augmented 26.38 2.27 26.17 8.89

Depleted 23.38 9.16 30.80 6.14

Balanced 23.53 7.15 31.14 9.23

PA Scale 3

Augmented 26.56 7.66 28.83 10.76

Depleted 24.56 7.62 34.80 4.09

Balanced 24.35 7.37 31.00 12.52

PA Scale 4

Augmented 26.63 8.50 24.00* 8.67

Depleted 24.25 6.66 35.00 4.90

Balanced 25.12 7.21 31.29 10.13 Tryptophan 94

PA Scale Scores Female Male Meal Type M SD M SD

PA Scale 5

Augmented 25.88 8.45 28.50 7.79

Depleted 24.69 8.30 36.80 5.50

Balanced 24.41 9.10 30.00 7.57

PA Scale 6

Augmented 28.38 8.29 31.33 6.53

Depleted 25.75 8.42 32.60 3.78

Balanced 25.76 10.65 29.00 12.82

*p =.05 Tryptophan 95

participants. The assumption of homogeneity of variance was violated, however, necessitating the use of the Brown-Forsythe F correction for unequal group sizes; the

Brown-Forsythe correction is a robust test of the equality of means. Using this correction, the main effect of meal type on total words recalled was not significant [F(2,

12.07) = .73, p =.493, partial η2= .07].

An identical ANOVA was also conducted to examine the effect of meal type on

Rey-O Delayed Recall scores for females. The main effect of meal type on the number

of elements correctly recalled during the long-delay recall trial was not significant [F(2,

47) = .22, p =.806, partial η2= .01]. This same analysis was conducted for the male

participants, wherein a significant main effect of meal type was found [F(2, 20) = 5.21, p

=.015, partial η2= .34]. Post-hoc comparisons indicate that males in the Depleted

condition scored significantly higher on the Rey-O Long Delay subtest than did those in

the Balanced condition (see Table 12 for mean scores on the CVLT Long Delay Free and

the Rey-O Long Delay split by gender and meal type).

Taken together, the prediction that depletion would result in lower scores on

measures of LTM was not met. In fact, males in the Depleted group scored significantly

higher than did males in the Balanced condition and higher (though not significantly)

than those in the Augmented condition on Rey-O Long Delay Recall, a measure of

visuospatial LTM.

Hypothesis 2: Depletion will result in lower mood scores.

This prediction was tested by conducting a repeated measures ANOVA with the

NA and PA scores from all six administrations of the PANAS. Although this measure

was used to assess the efficacy of the tryptophan manipulation, it was also employed in Tryptophan 96

Table 12

Mean and Standard Deviation of Test Scores on the CVLT Long Delay Free Recall and the Rey-O Long Delay by Gender and Meal Type

Test Female Male Meal Type M SD M SD

CVLT-Long Delay

Augmented 13.65 2.18 11.63 4.14

Depleted 13.38 2.34 13.14 2.12

Balanced 13.24 7.05 13.13 1.55

Rey-O Long Delay

Augmented 21.88 7.15 21.06 c 4.28

Depleted 20.50 5.68 25.21a 5.71

Balanced 20.65 7.05 16.63 b 5.44 a p <.05 Significantly different from b but not significantly different from c; b is not significantly different from c. Tryptophan 97

examining the prediction that tryptophan depletion will lower mood scores as it directly

measures changes in self-reported affect throughout the testing session. The prediction

was also assessed by conducting an ANOVA with the Positive and Negative Interference scores for the Emotional Stroop.

As detailed in the repeated measures ANOVA described in the Effects of the

Tryptophan Manipulation section, four analyses were conducted looking at the NA and

PA scales of the PANAS for each gender separately. There were no significant main effects for NA or for meal type, nor were there any significant interactions between NA and meal type for either the females or the males. For the PA analysis, no significant main effects were found for PA or for meal type for either gender, nor were there significant interactions between PA and meal type for females. There was, however, a significant interaction between PA and meal type for the males on the 4th administration

of the PANAS. This interaction, although significant, is not interpretively meaningful.

An ANOVA of meal type on Emotional Stroop Negative Interference scores was

conducted for each gender. No significant main effect was found for meal type on

negative interference scores for females [F(2, 47) = .11, p =.899, partial η2= .01], or for

males [F(2, 20) = .14, p =.874, partial η2= .01].

An identical set of analyses were conducted using the Positive Interference score

of the Emotional Stroop. The main effect of meal type on positive interference scores

was not significant for females [F(2, 47) = .79, p =.459, partial η2= .03], or for males

[F(2, 20) = .02, p =.985, partial η2= .00] (see Table 13 for mean scores on the Positive

and Negative EStroop test split by gender and meal type). Tryptophan 98

Table 13

Mean and Standard Deviation of Test Scores on the Negative and Positive EStroop by

Gender and Meal Type

Test Female Male Meal Type M SD M SD

EStroop Negative Interference

Augmented 10.06 6.18 5.38 5.55

Depleted 9.31 6.67 4.43 5.38

Balanced 8.88 9.24 3.88 6.45

EStroop Positive Interference

Augmented 5.35 6.97 1.50 6.55

Depleted 3.06 6.88 1.86 4.10

Balanced 6.29 8.64 2.00 6.37

Tryptophan 99

Taken together, these analyses indicate that the prediction that those in the

Depletion group would score lower on measures of mood was not met.

Hypothesis 3: Augmentation will lead to lower scores on measures of working memory.

To assess this prediction, participants’ total raw scores for Letter-number

Sequencing, verbal fluency and Digit Span (total score on the second administration)

were converted into z-scores which were then averaged to arrive at a composite working

memory score for each participant. An ANOVA was conducted examining the effect of

meal type on the working memory composite scores for females. There was no

significant main effect of meal type on working memory scores [F(2, 47) = 1.29, p =.286,

partial η2= .05]. The same analysis was conducted for males, indicating that the main effect of meal type on working memory scores was not significant [F(2, 20) = .18, p

=.837, partial η2= .02] (see Table 14 for mean scores on the working memory composite

split by gender and meal type). Thus, the prediction that those in the Augmented

condition would obtain lower scores on measures of working memory was not met.

Hypothesis 4: Augmentation will result in functional improvements within the areas of

attention and vigilance.

To test this prediction, a composite attention score was created for each participant. This was done by converting raw scores for the measures of attention into z- scores and averaging them to arrive at a composite attention score for each participant.

The following tests were included in this composite score: Digit Span total score (from the second administration); Letter-number Sequencing total score; Digit-symbol Coding total score; Ruff 2 & 7 Total Speed and Total Accuracy scores; Trails A time; and Trails Tryptophan 100

Table 14

Mean and Standard Deviation of Test Scores on the Working Memory Composite by

Gender and Meal Type

Working Memory Composite Score Female Male Meal Type M SD M SD

Augmented .13 .64 .03 .92

Depleted -.01 .89 .29 .86

Balanced -.27 .63 .04 1.04

Tryptophan 101

B time. An ANOVA of meal type on composite attention scores was conducted for the

females. Results of this analysis revealed no significant main effect of meal type on

attention composite scores [F(2, 46) = .10, p =.904, partial η2= .00]. The same analysis

was conducted for the males, again revealing no significant main effect of meal type on

attention composite score [F(2, 19) = .80, p =.464, partial η2= .08] (see Table 15 for mean

attention composite scores split by gender and meal type). Thus, the prediction that

Augmentation would result in functional improvements in attention and vigilance was not

met.

Hypothesis 5: The balanced group will score higher than the depletion group on LTM

and on mood indices, and higher than the augmentation group on working memory.

These hypotheses, which were tested via the analyses for Hypotheses 1 through 3

(detailed above), were not met as neither females nor males in the Balanced group

obtained statistically significant higher scores than those in the Depleted or Augmented

groups on these measures. Females in the Balanced group did not score higher than the

females in the Depletion group on the CVLT Long-delay Free Recall [F(2, 47) = .13, p

=.882, partial η2= .01]. Similarly, there were no significant group differences between females on the Rey-O Delayed Recall [F(2, 47) = .22, p =.806, partial η2= .07]. Scores

on the CVLT Long-delay Free Recall were also not significantly different between males

in the Balanced and Depleted groups [F(2, 12.07) = .73, p =.493, partial η2= .01]. Scores

on the Rey-O Delayed Recall, however, were significantly different between males in the

Balanced and Depleted groups [F(2, 20) = 5.21, p =.015, partial η2= .34], with those in

the Depleted group obtaining higher scores than those in the Balanced group (see Table

12 for mean scores). Overall, the prediction that the Balanced group would score higher Tryptophan 102

Table 15

Mean and Standard Deviation of Test Scores on the Attention Composite by Gender and

Meal Type

Attention Composite Score Female Male Meal Type M SD M SD

Augmented -.00 .54 .10 .39

Depleted .03 .48 -.02 .35

Balanced .06 .37 -.17 .49

Tryptophan 103

than the Depleted group on measures of LTM was not met. In fact, males in the

Balanced group scored significantly lower than those in the Depleted group on the Rey-O

Delay Recall, a measure of visuospatial LTM (see Hypothesis 1 for further details).

The hypothesis that those in the Balanced group would obtain higher scores in

the mood indices was also not met. Neither the females [F(2, 46) = .08, p =.923, partial

η2= .00] nor the males [F(2, 16) = .51, p =.611, partial η2= .06] in the Balanced group

scored higher than those in the Depletion group on the NA scale of the PANAS.

Similarly, there were no group differences on the PA scale for the females [F(2, 46) =

.59, p =.599, partial η2= .03] or for the males [F(2, 15) = .66, p =.530, partial η2= .08].

Females in the Balanced group also failed to score higher than the Depletion group on the

Emotional Stroop Negative [F(2, 47) = .11, p =.899, partial η2= .11] or Positive [F(2, 47)

= .79, p =.459, partial η2=.03] Interference trials. Similarly, males in the Balanced group

failed to score higher than those in the Depletion group on either of the Negative [F(2,

20) = .14, p =.874, partial η2= .01] or Positive [F(2, 20) = .02, p =.985, partial η2= .00]

Interference trials of the Emotional Stroop (see Table 13 for mean scores). Taken together, these analyses demonstrated that the Balanced group did not score higher than

the Depletion group on mood indices (see Hypothesis 2 for further details).

The hypothesis that those in the Balanced group would score higher than those in

the Augmented group on measures of working memory was also not met for either the

females F(2, 47) = 1.29, p =.286, partial η2=.05] or the males [F(2, 20) = .18, p =.837,

partial η2= .02] (see Table 14 for mean scores; see Hypothesis 3 for further details).

Overall, hypotheses made in Hypothesis 4 were not met as neither the females nor

the males in the Balanced group obtained statistically significantly higher scores than Tryptophan 104

those in the Depleted group on measures of LTM and mood, and they did not obtain statistically significant higher working memory scores than those in the Augmented

groups.

Hypothesis 6: The balanced group will score lower than those in the augmentation group

on tests of attention and vigilance.

As discussed in the ANOVA of meal type on attention composite scores detailed

in Hypothesis 4, neither the females [F(2, 46) = .10, p =.904, partial η2= .00] nor the

males [F(2, 19) = .80, p =.464, partial η2=.08] in the Balanced group obtained a lower

score on tests of attention and vigilance than did those in the Augmented group (see

Table 15 for mean scores; see Hypothesis 4 for greater details). Thus, this hypothesis

was not met as there were no statistically significant between group differences on the

attention composite.

Exploratory Analyses

Exploratory analyses were also conducted in order to assess whether there were

any group differences on the other cognitive measures comprising the composite scores

or on the individual items of the PANAS. As the nature of exploratory analyses is to

examine whether any findings emerge that would warrant further exploration in future

research, no corrections for multiple comparisons were conducted; we were more

concerned with Type II error (i.e., sensitivity) than with Type I error (i.e., specificity) (S.

Miller, personal communication, March 17, 2010). In keeping with previous analyses, females and males were analyzed separately. Tryptophan 105

In an exploratory way, the individual items of the PANAS were analyzed in order to examine the individual affects (e.g., upset, interested, enthusiastic) captured by the

PANAS. As initial exploratory analyses, a MANOVA was conducted for each gender examining the effect of meal type on the difference scores for each item. The difference scores were created by subtracting the score on PANAS Time 6 from the score on

PANAS Time 1 for each individual item, resulting in 20 difference scores, one for each item on the PANAS. No significant between group differences emerged for females for any of the items (see Table 16).

This analysis was repeated for the male participants. A significant between group difference was found for males on the Excited difference scores [F(2, 16) = 3.81, p

=.044, partial η2= .32] (see Table 17). Post-hoc comparisons indicate that the Excited item was significantly different between the Balanced and Depleted groups, t(16) = 2.51, p =.023, r =.47.

In order to determine whether or not the individual items on the PANAS were in fact stable and reliable across time, test-retest reliability analyses were conducted on the

NA scale as prior research has found the NA scale to be the most sensitive to tryptophan manipulation. These analyses, which were conducted on the Balanced group, demonstrated that the NA is in fact stable over time, r = .78, p <.01. Further examination revealed that the Excited item is also reliable over time, with an average correlation of r

=.72 (when collapsed across gender) or of r =.80 (when only males are included). As difference scores have an inherently greater degree of error in them compared to repeated measures analyses, it was unclear whether there was, in fact, a change in excitement levels over time. For this reason, a repeated measures ANOVA was conducted on meal Tryptophan 106

Table 16

MANOVA for Each PANAS Item for Females

PANAS Item df F partial η2 p

Interested 2 .22 .01 .807

Distressed 2 2.29 .09 .113

Excited 2 .08 .00 .921

Upset 2 .14 .01 .870

Strong 2 .27 .01 .767

Guilty 2 .24 .01 .791

Scared 2 .04 .00 .965

Hostile 2 .97 .04 .386

Enthusiastic 2 .22 .01 .801

Proud 2 .19 .01 .827

Irritable 2 1.44 .06 .248

Alert 2 .40 .02 .674

Ashamed 2 .18 .01 .839

Inspired 2 .03 .00 .966

Nervous 2 .76 .03 .474

Determined 2 .25 .01 .784

Attentive 2 .54 .02 .588

Jittery 2 .02 .00 .982

Active 2 .85 .04 .432

Afraid 2 .05 .00 .951 Error 46 Tryptophan 107

Table 17

MANOVA for Each PANAS Item for Males

PANAS Item df F partial η2 p

Interested 2 .23 .03 .794

Distressed 2 .95 .12 .408

Excited 2 3.81 .32 .044

Upset 2 1.75 .18 .206

Strong 2 1.44 .15 .266

Guilty 2 .84 .10 .449

Scared 2 .61 .07 .556

Hostile 2 2.02 .20 .165

Enthusiastic 2 1.30 .14 .301

Proud 2 2.58 .24 .107

Irritable 2 1.01 .11 .385

Alert 2 .31 .04 .739

Ashamed 2 .26 .03 .777

Inspired 2 .68 .08 .521

Nervous 2 1.16 .13 .338

Determined 2 1.30 .14 .300

Attentive 2 .22 .03 .809

Jittery 2 1.22 .13 .321

Active 2 1.16 .13 .340

Afraid 2 1.10 .12 .358 Error 16 Tryptophan 108

type on Excited scores for all 6 times (male participants only). Mauchly’s test of

sphericity indicated that the assumption of sphericity had been violated for the main

effect of Excited, χ²(14) = 27.72, p =.017. Thus, degrees of freedom had been corrected

for using Greenhouse-Geisser estimate of sphericity (ε = .65 for the main effect of

Excited). There was no significant main effect for Excited [F(3.24, 51.88) = .53, p =.677,

partial η2= .03]. The main effect of meal type was also not significant [F(2, 16) = 2.64, p

=.102, partial η2= .25], nor was the interaction between Excited and meal type [F(10, 80)

= 1.49, p =.158 , partial η2= .16] (see Table 18 for mean Excited scores by meal type over

time).

Although the overarching omnibus analysis was not significant, post-hoc

comparisons were examined for exploratory purposes to see if any trends existed within

the data. Post-hoc comparisons indicate that the Excited item was significantly different

between the Augmented and Depleted groups on Time 4, t(16) = -2.74, p =.015, r = 0.75,

Time 5, t(16) = -2.14, p =.048, r = 0.47, and on Time 6, t(16) = -2.12, p =.050, r = 0.47.

These post-hoc comparisons indicate a trend wherein those in the Depleted group

experienced a fairly modest, but linear, increase in excitement level over time, whereas

excitement was lowered between administration two through four before increasing

drastically by the sixth administration for those in the Augmented group. Participants in

the Balanced condition demonstrated a subtle decrease in excitement levels over time

(see Figure 2 for mean Excited scores by meal type over time).

Taken together, these analyses suggest that there is a trend between meal type and

level of excitement, indicating that those in the Depleted group experienced an increase

in level of excitement as the study progressed, whereas those in the Augmented group Tryptophan 109

Table 18

Mean and Standard Deviation of Excited Item Over Time for Males

Administration Meal Type M SD

Excited 1

Augmented 2.00 .63

Depleted 3.00 .89

Balanced 3.14 1.07

Excited 2

Augmented 2.50 .84

Depleted 3.00 1.27

Balanced 3.00 1.16

Excited 3

Augmented 2.17 1.33

Depleted 3.17 .41

Balanced 3.00 1.29

Excited 4

Augmented 1.83 .98

Depleted 3.50 .55

Balanced 2.71 1.38

Tryptophan 110

Administration Meal Type M SD

Excited 5

Augmented 2.50 .84

Depleted 3.67 .82

Balanced 2.71 1.11

Excited 6

Augmented 2.50 .84

Depleted 3.67 .52

Balanced 2.57 1.27

Tryptophan 111

Figure 2. Mean Excited scores by meal type over time.

4

3.5

3 Augmented Balanced 2.5 Depleted Mean Scores

2

1.5 PANAS 1 PANAS 2 PANAS 3 PANAS 4 PANAS 5 PANAS 6 Administration Tryptophan 112

experienced a dip in excitement levels followed by a steady increase in excitement

towards the latter half of the testing session. The subtle decrease in excitement

experienced by the Balanced group over time was not statistically significant. These

findings may provide some limited evidence for the effect of the manipulation.

Oneway ANOVAs were conducted on all other tests and measures employed in

this study in order to examine the effect of meal type on neuropsychological and

emotional performance; females and males were analyzed separately. As can be seen in

Table 19, the only significant result was found for male participants on the Ruff 2 & 7

Total Speed subtest [F(2, 20) = 4.68, p =.022, partial η2= .32]; all other analyses failed to

reject the null hypothesis. Post-hoc Bonferroni comparisons on the Ruff 2 & 7 Total

Speed subtest revealed significant differences in mean time scores between the

Augmented and Balanced groups but not between the Augmented and Depleted groups, or between the Balanced and Depleted groups. The Augmented group obtained a mean speed score of 112.50 (SD = 16.44), the Balanced group obtained the fastest speed score, with a mean score of 88.38 (SD = 17.44), and the Depleted group obtained a mean speed score of 104.86 (SD = 13.91). There was no significant difference in time scores between the Augmented and the Depleted group, or on any other measures for either females or males.

Discussion

In this study, the effects of tryptophan manipulation on cognitive functioning and affective state were examined. More specifically, a dietary method of tryptophan manipulation was employed in order to assess any differences in performance produced by tryptophan augmentation as compared to tryptophan depletion or balanced tryptophan Tryptophan 113

Table 19

ANOVAs on the Effect of Meal Type on All Test Measures Examined in Exploratory

Analyses, Separated by Gender

Test df F partial η2 p

Digit Symbol Coding Female 2, 47 .13 .01 .878 Male 2, 20 1.26 .11 .305

FAS Female 2, 47 .71 .03 .495 Male 2, 20 1.16 .10 .334

Letter Number Sequencing Female 2, 47 .87 .04 .425 Male 2, 20 .22 .02 .808

Stroop Interference Female 2, 44 .25 .01 .783 Male 2, 18 .15 .02 .865

Ruff 2 & 7 Total Accuracy Female 2, 46 .86 .04 .428 Male 2, 19 2.00 .17 .163

Ruff 2 & 7 Total Speed Female 2, 46 .12 .01 .890 Male 2, 20 4.68 .32 .022

Trails A Time (sec) Female 2, 47 3.16 .12 .052 Male 2, 20 2.01 .17 .160

Trails B Time (sec) Female 2, 47 .66 .03 .521 Male 2, 20 1.03 .09 .374

Digit Span 2 Total Female 2, 47 .98 .04 .383 Male 2, 20 .24 .02 .787

Tryptophan 114

levels. Although the cognitive measure of pre-test/post-test differences (Digit Span

Backwards) failed to detect any significant between group differences for either males or

females, there were marginally significant group differences in positive affect between

males in the Augmented and Depleted group. These differences in PA levels seem to be

primarily driven by the trend in excitement levels between males in the Augmented and

Depleted conditions over time. Group differences were also found for the males on a

visuospatial measure of long-term memory, as well as on a measure of attention and concentration. Results of this study support the hypothesis that dietary manipulations aimed at altering tryptophan levels had an effect on some cognitive tests and positive affect, at least with regards to males.

Did the manipulation affect affect?

Of all the measures employed in this study, it was believed that the PANAS would be the most sensitive to tryptophan manipulation and it can thus be viewed as a check on the efficacy of the manipulation. Although no significant results emerged on the NA scale for either the males or the females, indicating that participants reported no change in negative affect, a marginally significant finding emerged for males on the PA scale, but not for females. More specifically, it was found that on the fourth administration of the PANAS (which was administered immediately after lunch), males in the Depleted group scored higher on the PA scale than did males in the Augmented group. As only one of the six administrations demonstrated a near-significant effect of meal type, with all others being not significant, it is likely that this finding is spurious and not interpretively meaningful. Thus, despite this trend, no meaningful results emerged on either the NA or the PA scale for either the females or the males, indicating that Tryptophan 115

participants reported no increase or decrease in overall negative or positive affect. This

finding was somewhat unexpected as it was predicted that negative affect (i.e. NA scale

scores) would be affected, whereas a subtle change in positive affect was actually found.

The results of the study by Luciana and colleagues (2001), however, are the

opposite as they found that tryptophan depletion resulted in transient decreases in negative affect, and a lowering of positive affect, whereas tryptophan augmentation had

no effect on negative affect, but lowered positive affect. Their findings seem to indicate

that positive affect can be decreased by either augmentation or depletion of tryptophan,

whereas the effect on negative affect is transient at best. This is in contrast to the finding

by several researchers that negative affect is most affected by augmentation of

serotonergic transmission (and thus, presumably, tryptophan; e.g., Bodkin et al., 1997;

Shelton & Brown, 2000; Shelton & Tomarken, 2001), which would indicate that increased serotonin likely plays a role in reducing feelings of general distress (Dichter et al., 2005). Reviewing the literature on the effects of tryptophan manipulation on mood and affect, however, illustrates that there is no consensus within the field. For instance, many researchers have found no effect of tryptophan manipulation on mood (e.g.,

Hughes et al., 2003; Park et al., 1994; Shansis et al., 2000; Smith et al., 1988), whereas many others have found that tryptophan depletion lowers mood (e.g., Benkelfat et al.,

1994; Luciana et al., 2001; Riedel et al., 1999; Schmitt et al., 2000; Spring et al., 1983;

Young et al., 1985).

One possible reason for the lack of an effect of tryptophan manipulation on NA scores in the present study is that perhaps the manipulation was not as strong as expected.

Another possibility is that the inclusion of a macronutrient-manipulated breakfast, lunch Tryptophan 116

and snack for each participant lessened (or even perhaps eradicated) the effects of

tryptophan manipulation on negative affect. For instance, many of the studies within the

literature include only a macronutrient-manipulated breakfast or lunch and few include

snacks (e.g., Fischer et al., 2002; Riedel et al., 1999; Spring et al., 1983; Wurtman et al.,

2003). This makes comparison between studies difficult as each study will thus report

differing amounts of carbohydrates, proteins, fats and calories in their meals. For

instance, Wurtman and colleagues employed breakfasts in their study and reported a total

of 175.70 calories for the high carbohydrate meal, and 34.29 calories for the high protein

meal. In the present study, those in the Augmented condition (i.e., high carbohydrate

condition) ingested 931 calories in total, whereas those in the Depleted condition (i.e., the

high protein condition) consumed a total of 881 calories. Since the present study

included two meals and a snack, the calorie intake was thus much higher, making it

difficult to determine whether the manipulation was too weak, or whether there were too

many competing macronutrients for subtle differences in affect to emerge.

An alternative possibility for the lack of an effect of tryptophan manipulation on

negative affect is that perhaps macronutrient content does not exert a strong influence in

the first place, which would consequently make detecting changes difficult. In line with

this notion, Teff, Young and Blundell (1989) reported that a carbohydrate meal containing as little as 4% protein will counteract the rise in availability of tryptophan to the brain that would otherwise occur. However, in a study that sampled lumbar cerebrospinal fluid from 3 normal pressure hydrocephalus patients, Teff, Young,

Marchand, and Botez (1989) found that neither carbohydrates nor protein, ingested 2.5 hours prior to lumbar puncture, resulted in significantly altered levels of central nervous Tryptophan 117

system tryptophan or serotonin. While it is possible that this conclusion was the result of

either too little time elapsing between treatment and measurement of the effect, by the

small sample size, or by the sample characteristics (i.e., normal pressure hydrocephalus patients), it does raise the question of how much of a given macronutrient is required to

influence tryptophan or serotonin levels in the brain and spinal cord, and over what time

is this change detectable? In a more recent study by Lindseth, Petros, Jensen, Lindseth

and Fossum (2006) that examined the effects of macronutrients on the flight performance

of pilots, it was found that a high-fat diet resulted in significantly better performance than

the high-carbohydrate, high-protein or control diets. Furthermore, they concluded that when on the high-protein diet, pilots performed the worst. These contradictory findings suggest that the effects of protein (or carbohydrates) on tryptophan availability are not straightforward. In the present study, the Augmented group had 15% of its total caloric intake comprised of protein, whereas the Balanced meal only had 2% of it’s calories coming from protein. In consideration of the findings by Teff, Young and Blundell, the

Balanced group should have displayed some effect of tryptophan manipulation given that there was not enough protein to quash the emergence of tryptophan-driven effects.

Regarding the statement by Teff, Young, Marchand, and Botez, however, both groups should have demonstrated some effect of tryptophan based solely on the premise that protein content does not appear to matter. Fischer and colleagues (2002) had concluded that their lack of tryptophan-related findings was due to a protein content in the meals that was still too high, based on the idea that even 4% protein would abolish effects; the

same could possibly be said for the present study regarding the Augmented group.

However, we are not convinced that this is the case in the present study as there appears Tryptophan 118

to be no clear consensus on how much protein is required, if any at all, to erase

tryptophan-mediated effects on affect (or cognition). Further, S. N. Young (1993) states

that, “[s]ince few meals eaten by humans will contain less than 4% protein, serotonin-

mediated changes in behaviour after carbohydrate meals are unlikely to be a normal physiological phenomenon” (p. 240).

A final possible reason for the lack of findings of an effect of tryptophan

manipulation on NA scores pertains to screening criteria as it seems likely that the

exclusionary criteria used during recruitment would play a critical role in the outcome.

For instance, previous studies have found differing effects of tryptophan manipulation on

mood when studying those with a family history of depression (e.g., Riedel et al., 1999),

personal history of mood disorder (e.g., Price, Charney, Delgado & Heninger, 1991; S. N.

Young, 1993), stress level (e.g., Markus et al., 1998), and even age or gender (Spring et

al., 1983). The present study employed very rigorous exclusionary criteria which makes

it possible that it over-controlled for potential confounding factors, thereby decreasing the

likelihood that any effect would emerge. While this certainly reduces the likelihood of

making a Type I error, it begs the question as to whether the over-stringent controls made

it difficult for more subtle effects to be detected (i.e., Type II error). Reviewing the

literature, it is clear that there is no standard set of exclusionary criteria for this line of

research. For example, the requirements for many studies were merely being ‘healthy’

and free from medication/drug use (e.g., Blum et al., 1992; Coull et al., 1995; Park et al.,

1994). Some studies did not list exclusion criteria at all, only stating that participants

were interviewed about their medical and/or psychiatric history (e.g. Lyons & Truswell,

1988; Wurtman et al., 2003). On the other hand, some studies employed very strict Tryptophan 119

controls similar to those used in the present study (e.g., Luciana et al., 2001; Riedel et al.,

1999; Schmitt et al., 2000) and still found effects of the tryptophan manipulation on

affect (and cognition). All of these studies, however, employed within-subjects designs and all (with the exception of Fischer and colleagues, 2002) utilized an amino acid

tryptophan depletion protocol. The present study utilized a mixed design with a dietary

manipulation of tryptophan. Thus, it is possible that the use of strict exclusionary

criteria, in conjunction with the mixed design and dietary tryptophan manipulation

employed in the present study, prevented the emergence of affective differences. The

mechanism behind such action, however, is still unclear as there are others within the

literature who found effects of tryptophan using a dietary manipulation, including those

who employed between-subject designs but who did not utilize strict exclusionary criteria

(e.g., Spring et al., 1983). Thus, there is some degree of interplay between these three

factors (controls, design and mode of manipulation) that influences whether or not effects

on mood are detected. As more research is conducted within this field, a consensus

should begin to emerge that will indicate which methods and controls provide the most

accurate and replicable results as to the effect of tryptophan on positive and negative

affect.

With regards to specific affects comprising the NA and the PA scales, exploratory

repeated measures analyses of individual affects on the PANAS detected a trend for

males, indicating group differences in levels of excitement on the fourth, fifth and almost

the sixth administrations; no significant group differences were found for either gender

on any of the individual affects. More specifically, it was found that those in the

Depleted group demonstrated a fairly linear (albeit modest) increase in excitement over Tryptophan 120 time, whereas those in the Augmented group demonstrated a dip in excitement from administration two through four before experiencing a drastic increase in excitement by time six. A limitation of exploratory analyses is that the risk of committing a Type I error

(i.e., of finding a result that is not really there by rejecting the null when it is actually true) is increased. It is possible that this is the case in the present study as it is difficult to interpret, from a theoretical perspective, the reason for increased excitement levels in males in the Augmented and Depleted conditions, the two conditions in which participants received opposite carbohydrate:protein proportions in their meals, whereas those in the Balanced condition demonstrated a minor decrease in excitement levels.

Since this finding was not predicted from the outset and does not have a theoretical basis to support it, any interpretation must be handled with caution. Regardless, one possible explanation is that perhaps it is not the macronutrient content per se, but rather the ingestion of greater than normal amounts of dietary components (i.e., carbohydrates or proteins) that is driving this finding, which could also explain why those who received a balanced diet demonstrated a minor decrease in level of excitement. This decrease would not be surprising when one considers that participants were in the lab from 8:45am until roughly 2pm, a span of approximately 5 hours, during which time it would seem plausible that activity levels and the degree of alertness would decrease. It is difficult to maintain a high level of arousal over an extended period of time, so the body naturally begins to lower its degree of arousal in response. In the current sample, however, the average score (collapsed across gender and meal type) on the Alert item at time 6 was

3.43 (out of 5), indicating a ‘Moderate’ degree of alertness, which is actually slightly higher than the average rating of 2.75 (out of 5) that indicated only a ‘Slight’ degree of Tryptophan 121

alertness at the start of the study. In a similar vein, scores on the Active item did not

decline over time, with an average score of 2.24 (out of 5) on the sixth administration,

compared to an average score of 2.68 (out of 5) on the first administration. These results

show that in fact, a minor increase in levels of alertness and activity were found over

time, not the expected decrease.

With regards to why the Excited item would be most sensitive to the manipulation, as opposed to the PA scale in general, it has been reported by Watson,

Clark and Carey (1988), that “[p]ositive affect is a dimension reflecting one’s level of

pleasurable engagement with the environment” (p. 347). Excitement can also be seen as

a pleasurable state of being – we get excited about events to come, or about things we are

presently experiencing. As to why there would be differing levels of excitement over

time for the different meal types, however, is somewhat more difficult to understand.

Recall that in the present study significant differences between the Augmented and the

Depleted group were found for level of excitement at Time 4, Time 5 and almost at Time

6 (for males only), with those in the Depleted group displaying the greatest levels of

excitement at all times. More specifically, Time 4 represents the fourth administration of

the PANAS, which was completed immediately after lunch, and Time 5 (i.e., the fifth

administration) was immediately before the test battery began. Immediately after lunch,

those in the Augmented group experienced the lowest levels of excitement which might

be explained by the finding that carbohydrate-rich foods result in decreased feelings of

dysphoria, alertness and general distress, and increased feelings of calmness

(Christensen, 1993; Christensen, Krietsch, & White, 1989; Pühringer, Wirz-Justice, Graw,

LaCoste & Gastpar, 1976; Spring et al., 2008). Recall that carbohydrate consumption Tryptophan 122 leads to increased insulin secretion which acts to draw the large neutral amino acids

(LNAAs), with the exception of tryptophan, into the surrounding tissue. This action enables tryptophan to pass through the blood brain barrier with little competition, where

5-HTP synthesis occurs, which is immediately converted into serotonin. This process results in increased serotonin synthesis and activity within the limbic system, including the amygdala and the prefrontal cortex, which in turn produces a feeling of calmness and even euphoria (Pühringer, et al., 1976). It is also known that 5-HTP raises endorphin levels in the brain and endorphins act as the body’s natural defense against pain and stress of all kinds (physical, psychological, and emotional) (Murray, 1998). Thus, greater levels of 5-HTP in the brain result in more endorphins being released, which in turn decreases feelings of stress (Murray, 1998). This decrease in stress could in turn result in decreased levels of excitement.

Conversely, the (male) Depleted group in the present study experienced higher levels of excitement over time than did the Augmented group, which seems indicative of greater sympathetic nervous system arousal. In the present study, the depleted meal was composed of the lowest level of carbohydrates and the highest level of protein (57 g of carbohydrates and 39 g of protein, compared to 200 g of carbohydrates and 11 g of protein in the Augmented condition); thus, it should be expected that the effects of the depleted meal would be opposite to those of the augmented meal. The finding that those in the Depleted group experienced the highest levels of excitement over time could be interpreted to indicate that protein increases one’s level of excitement. Ingestion of protein has also been linked with self-reported ratings of happiness. For instance, Verger,

Lagarde, Batejat and Maitre (1998) stated that participants reported feeling happier after Tryptophan 123

consuming a protein meal than after a ingesting a protein-free meal. However, a study by

DeCastro (1987) reported the opposite result from protein consumption. In his study he

had participants keep a detailed food diary for 9 consecutive days and found that over the

9-day period those who reported a protein-rich diet also reported greater overall levels of depression. Reconciling these divergent findings is difficult and likely stems from differing samples, designs and methodologies.

As should be clear, the findings pertaining to the relationship between protein, carbohydrates and mood are not entirely straightforward as several researchers have noted that although ingestion of simple carbohydrates leads to increased feelings of energy in the short-term (e.g., Blouin et al., 1991; Thayer, 1987), in the long-term they result in increased feelings of fatigue and lower energy levels (e.g., D. P. Wyons & I.

Wyons, unpublished data). Further, as discussed earlier, protein has been found to influence feelings of happiness and depression (DeCastro, 1987; Verger et al., 1998). In the present study, participants in the Augmented condition consumed carbohydrates for an extended period of time (breakfast, lunch and a snack), resulting in decreased excitement levels following the morning snack. The Depleted group, however, exhibited a subtle increase in excitement levels over time. By contrast, those in the Balanced group, whose meals contained carbohydrate:protein ratios between those ingested by the other two groups, demonstrated a minor decrease in excitement over time. While it is not clear from the literature exactly what effect specific macronutrients have on excitement levels, it has generally been found that increases in negative mood typically follow the consumption of lunch (Craig, 1986; Kanarek, 1997). This conclusion was supported by males in the Augmented condition of the present study. Nonetheless, these Tryptophan 124

interpretations must be made with caution as there are many factors that can influence these findings, including the size of the meal, it’s caloric and macronutrient content, whether the participant is a habitual breakfast-eater, and whether the foods ingested were similar to those normally consumed by participants at home (Kanarek, 1997; Lloyd,

Rogers, Hedderley, & Walker, 1996). It is evident that further research within the area of the effects of specific macronutrients on individual affects is needed before a clearer picture can begin to emerge.

Overall, the effect of macronutrients on specific affects or scales is not clear within the literature. For instance, Lieberman and colleagues (1983) found that tryptophan resulted in reduced alertness, as measured by the Visual Analogue Mood

Scale (VAMS), whereas scores on the fatigue-inertia scale of the POMS were increased and scores on the vigor-activity scale of the POMS were decreased. In a later study conducted by Lieberman (Lieberman et al., 2002), carbohydrates were found to increase alertness and decrease scores on the confusion scale of the POMS. These results seem contradictory in light of the fact that carbohydrate consumption has been shown to increase tryptophan levels in the blood (e.g., Fernstrom & Wurtman, 1971) and has been found to increase alertness by some researchers (Lieberman et al., 2002) and to decrease alertness by others (Lieberman et al., 1983). Thus, the results of Lieberman’s respective studies seem to indicate that tryptophan both increases and decreases levels of alertness.

Taken together, the results of the present study and those in the literature highlight the

need for more research examining not just positive and negative affect on the whole, but

specific affects as well, so that a greater understanding of the influence of tryptophan on

mood and affect can begin to emerge. Tryptophan 125

Did the manipulation affect cognitive functioning?

In an attempt to determine the effect of tryptophan manipulation on cognitive functioning, the present study employed measures aimed at testing the domains of memory (specifically long-term memory), attention/concentration, and executive functioning. The Digit Span Backwards was also utilized as a measure of the effectiveness of the manipulation as there is some evidence within the literature that it is sensitive enough to detect the effects of tryptophan manipulation (Kanarek & Swinney,

1990; Luciana et al., 2001). The present study, however, failed to replicate these findings. This result in and of itself does not necessarily indicate that the tryptophan manipulation did not work, but rather it may indicate that Digit Span Backwards may not be sensitive enough to detect these effects. This issue of test sensitivity has also been raised with regards to difficult to measure constructs such as attention. It has been suggested that paper-and-pencil tests such as those employed in the present study may not be sensitive enough to detect subtle changes in cognitive functioning produced by altered levels of brain tryptophan (e.g., Hoyland, Lawton & Dye, 2008; Shansis et al.,

2000). This argument does not hold in light of the fact that the CANTAB battery, which is known to be sensitive to subtle neuropsychological changes and which was employed by Hughes’s group (2003) and Park and colleagues (1994), has also failed to reliably detect tryptophan-induced changes in cognitive performance. Park’s group found that low levels of tryptophan resulted in poor consolidation of information, which in turn resulted in lower scores on measures of long-term memory and learning. Conversely, despite utilizing the exact same depletion methodology as Park, employing many of the same CANTAB tests, and recruiting a larger sample size, Hughes’s group failed to find Tryptophan 126 any significant effects of tryptophan depletion on neuropsychological performance, including long-term memory. Thus, it appears that even tests deemed to be highly sensitive to subtle changes in cognitive function, such as those produced by tryptophan manipulation, fail to produce replicable results. Hoyland and colleagues (2008) go one step further by stating that “[i]t is feasible that commonly employed tasks may be inadequate measures of performance that mask real effects” (p. 74). In their review of the macronutrient effects of food on cognition, they concluded that task difficulty seems to be the best indicator of task sensitivity in that tasks that require the greatest cognitive load are most sensitive to macronutrient manipulations.

Regardless, significant group differences were found on a visuospatial measure of

LTM. It was predicted that those in the Depletion group would score lower on measures of LTM. This prediction was in part supported by the finding that males in the Depleted group scored differently than the other two groups on LTM measures. The prediction that they would score lower, however, was not met as males in the Depleted group scored significantly higher than did males in the Balanced group on the Rey-O long delay recall; no effect was found for the males on the verbal LTM test, or for females on either the verbal or the visuospatial measure of LTM. The finding for the males on the Rey-O was somewhat unexpected for the simple reason that most researchers only measure verbal

LTM (e.g., Kaplan et al., 2001; Riedel et al., 1999; Schmitt et al., 2000), whereas those that do employ visuospatial measures of LTM (e.g., Hughes et al., 2003; Shansis et al.,

2000) find no effect of meal type. Both Hughes and Shansis, however, employed a within-subject design and used the amino acid protocol for altering tryptophan levels.

The present study employed a mixed-design, and used a dietary manipulation for Tryptophan 127 tryptophan. Thus, it is possible that the difference in findings could be related to methodology. In particular, it seems to bolster the notion broached earlier that extreme amounts of specific macronutrients could influence cognitive functioning, as the

Depleted group, who ingested low levels of carbohydrates but high levels of protein, performed significantly better than those in the Balanced group, who did not receive greater-than-normal amounts of protein (or carbohydrates). Indeed, Kaplan and colleagues (2001) state that “the ingestion of energy, regardless of source, appears to improve memory” (p. 691). They found that carbohydrates, protein and fat intake all improved delayed paragraph recall in their sample of elderly adults (aged 61-79), although protein in particular enabled participants to recall more details during the delay recall than on the immediate recall trial. Why this would be so is somewhat unclear. It is known, however, that protein-containing foods increase phenylalanine, from which tyrosine is synthesized (Curzon, 1985). Tyrosine, in turn, is the precursor to dopamine, norepinephrine and epinephrine, the latter two of which are known for their excitatory effect in readying the body for activity and for increasing alertness (Kolb & Whishaw,

1996; Spring, 1986). According to Lieberman and colleagues (1983), however, “tyrosine appears to have little or no effect on rested, unstressed volunteers” (p. 246). Dopamine, on the other hand, plays a role in memory by way of dopaminergic connections between the basal ganglia and substantia nigra (Kolb & Whishaw, 1996). Thus, it could be that the findings by Kaplan’s group are mediated by dopaminergic processes. Memory impairments for nonverbal stimuli, such as objects or drawings, however, are known to result from damage to the right temporal lobe and surrounding areas, including the amygdala, hippocampus, and prefrontal cortex (Kolb & Whishaw, 1996). As discussed Tryptophan 128

earlier, the hippocampus in particular plays a role in spatial memory as the memory and perceptual systems are closely linked (Zola & Squire, 2000). The thalamus also plays a role in memory in that connections between the temporal and prefrontal cortices pass

through the thalamus. Neocortical and brainstem systems, including acetylcholine,

serotonin and norepinephrine systems, all provide input to the temporal lobe and other

regions involved in memory processes (Kolb & Whishaw, 1996). Together, these

processes can lead to greater LTM for visuospatial information.

During exploratory analyses, a significant between-group difference was also

found for males on the Ruff 2 & 7 Selective Attention Test, with those in Augmented

group obtaining a faster speed score than those in the Balanced group; no difference was

found for females. A possible explanation for the findings with males could be due to

cerebellar function, as this area of the brain, although primarily thought of for its motor

control, is involved in speed of information processing (Botez et al., 1985). It does this

through its non-motor pathways, connecting to the thalamus and receiving input from the

frontal, parietal and superior temporal cortices (Schmahmann & Sherman, 1998). These

pathways also influence working memory (Desmond et al., 1997), as well as general

memory and learning (Nyberg, 1998). Together, these functions are all required in order to successfully complete the Ruff 2 & 7, as the speed with which the task is completed also requires being able to keep the rules of the task in working memory during completion. The majority of the serotonergic innervation to all layers of the cerebral cortex, including temporal, parietal, frontal and cerebellar cortices, comes from the dorsal raphe nuclei (Graeff, 1997; Molliver, 1987). Thus, a reduction to the amount of serotonin available to the structures would likely result from lesions to these cerebellar Tryptophan 129 pathways. Although it has been reported in the literature that the speed of information processing slows as a result of such lesions (e.g., Botez et al., 1985), it is not yet clear whether this outcome is due to decreased tryptophan or due to some other process influenced by such lesions. For instance, Smith and colleagues (1988) found that response times to peripheral stimuli on a visual search task were slowed following a high carbohydrate lunch (i.e., increased tryptophan), whereas those in the high-protein condition (i.e., reduced tryptophan) experienced greater distractibility to non-relevant stimuli. These results do not concur with those of the present study, which found faster response times for those in the Augmented (i.e., increased tryptophan) condition compared to those in the Balanced and Depleted conditions. An important difference between these studies, however, is that although both employed a dietary method of manipulating tryptophan, Smith’s group utilized a within-subject design, whereas the present study used a mixed-design. Furthermore, the present study analyzed each gender separately, whereas the study by Smith did not, resulting in a total sample size of 23 males in the present study, versus a mixed sample of 11 participants (5 males, 6 females) in the latter study. Regardless, the effect of tryptophan manipulation on visual search tasks is not unanimous within the literature. For instance, Fischer and colleagues (2002) reported transiently improved attention following carbohydrate consumption (although they concluded that the balanced and protein conditions resulted in better overall cognitive performance), whereas several groups have failed to find any effect of augmented or depleted tryptophan (Hughes et al., 2003; Luciana et al., 2001; Shansis et al., 2000). As with Smith’s group, the studies that failed to detect any between-group differences all employed a within-subjects design. As has been discussed previously, Tryptophan 130 reconciling the results of the present study with the findings in the literature is difficult due to the utilization of differing methods of manipulation and different research designs.

Thus, there are several possible reasons for such discrepancies between the present study and those reported in the literature. For instance, as has been discussed earlier, there appears to be no real consensus within the field as to the best way to manipulate tryptophan levels. There is ample evidence, as presented above, to suggest that at least within those studies that found significant results, the amino acid protocol is equally effective as the dietary (carbohydrate-loading) method at altering tryptophan levels. However, even among researchers using the same method, there is little consistency with regard to dose, with researchers employing macronutrient protocols ranging from 25g to 100g (e.g., Ford, Scholey, Ayre, & Wesnes, 2000; Green, Taylor,

Elliman, & Rhodes, 2001; Hughes et al., 2003; Park et al., 1994; S. N. Young et al.,

1985). Within the dietary literature, there is even less consistency with regards to dose or type of manipulation, with some studies employing carbohydrate or macronutrient drinks

(e.g., Kaplan et al., 2001; Lieberman et al., 2002), some utilizing full meals or foods (e.g.

Markus et al., 1998; Smith et al., 1988; Spring et al., 1983), and still others using cream- like pastes or puddings (e.g., Fischer et al., 2002; Teff, Young & Blundell, 1989). To further complicate matters, there is evidence that the time of day in which the protocol is administered, in conjunction with the age and gender of participants, also influences results (e.g., Craig, 1986; Spring et al., 1983). Researchers have also employed different delay periods between administration of the depletion method and testing session, which may also influence results. For instance, although Benkelfat and colleagues (1994) found that 5 hours are needed for tryptophan levels to reach their peak level of depletion Tryptophan 131 following the amino acid protocol, some researchers have tested participants 2 to 24 hours after the manipulation (e.g., Coull et al., 1995; Markus et al., 1998; Reidel et al.,

1999; Schmitt et al., 2000), whereas others have tested participants only 15-30 minutes after ingestion of the macronutrient drinks (e.g., Kanarek & Swinney, 1990; Kaplan et al.,

2001). Furthermore, some researchers have employed the use of maintenance doses throughout the testing session (e.g., Schmitt et al., 2000), and others still have made use of practice sessions in order to obtain baselines measures of performance (e.g., Fischer et al., 2002; Luciana et al., 2001; Riedel et al., 1999). It has been postulated by Hoyland and colleagues (2008) that the inability of researchers to successfully and consistently replicate the findings reported in the literature is likely due to these issues of varying methodologies. In other words, the paucity of research that employs the same tests and means of manipulation could be the very thing that is hindering progress within this field of research.

Bellisle (2001) and others have pointed out that there are a myriad of other factors that can influence test results. For instance, motivation, arousal, previous learning, time of day, fatigue, and individual characteristics and abilities could all lead to discrepant findings. Craig (1986) posits that both the quantity and the quality (i.e., the carbohydrate:protein ratio) of the meal is also important, as is the “nature and disposition” (p. 163) of the person consuming the meal, such that a person accustomed to eating large meals will be less affected by the macronutrient components of a large meal than would a be person who usually eats smaller meals. Further, he states that the amount of time between each meal is also likely to influence the outcome as someone who is hungry is likely to be more affected than is someone who is not hungry. This Tryptophan 132

reasoning could be extended to include metabolic rate, as someone with a fast

metabolism, who is used to eating more frequently, would likely react differently than would someone with a slower metabolism. Nonetheless, metabolism is a variable not often accounted for within the literature (but see Smith et al., 1988) and is typically excluded from analyses. Although the present study failed to detect any group differences for females or for males with regards to the average amount of time between each meal or snack (i.e., the eating frequency variable), it cannot be concluded that this

variable is unimportant. In the present study, participants were asked during the

screening session how many hours typically pass between each meal or snack, which is

admittedly an inaccurate measurement of metabolic rate, especially as participants

reported guessing how many hours passed as they could not pin down the exact amount of time (on average) between each meal. This could be a promising area of investigation

as metabolism would influence the digestion speed of the meals consumed such that

someone with a faster metabolism may have a different window of opportunity in which

to measure cognitive or affective changes than would someone with a slower metabolic

rate.

Individual differences in neurotransmitter synthesis and activity would also

presumably influence the effectiveness of tryptophan manipulation in that higher or lower

baseline levels would result in greater or lesser amounts of depletion or augmentation.

Along these lines, Steckler and Sahgal (1995) suggest that different and overlapping

neurotransmitter systems, such as the cholinergic and serotonergic systems, exert

different effects on cognitive processes and that manipulating availability of

neurotransmitters in one system could influence the other. In other words, a Tryptophan 133 compensatory process could emerge with one system taking over the function(s) of the incapacitated system until normal functioning is reestablished. This could become even more apparent when individual differences in these systems get taken into account.

Lastly, results of the present study also suggest that demographic variables may influence results to some degree and on some tests, a finding echoing that of Spring and colleagues (1983). Unlike the finding by Sambeth and colleagues (2007), who stated that females carried the effect for results of tryptophan manipulation on (verbal) LTM, the present study only found results for males (on visuospatial LTM). With regards to other demographic variables, it seems that the present study is one of the first to include demographic variables in the analyses. Certain variables, such as ESL status, BMI, and eating frequency, were found to exert no influence on test results. However, eating frequency, as discussed earlier with regards to metabolic rate, was not a well-designed measure so the results from this analysis are not entirely conclusive. Level of physical activity, however, did demonstrate some influence on cognitive performance for the females. It is possible that if data had been collected on a larger sample of males, and an interval level scale used instead of an ordinal scale, more significant findings would have emerged. Future research should be sure to employ continuous measurements of physical activity, as well as metabolic rate and other key variables, in order to ensure more accurate analyses of factors potentially influencing the effect of tryptophan manipulation on cognitive and affective measures.

Strengths of the Current Study

This study has several notable strengths, the first of which is the inclusion of an augmented condition. The majority of the studies in this field of research employ only a Tryptophan 134

depletion condition and a control (or, balanced) condition (e.g., Coull et al., 1995; Park et

al., 1994), whereas the present study included both a depleted and an augmented condition, in addition to a balanced condition, in order to facilitate greater understanding

of any between-groups difference that could emerge. What is more, our stratification of

participants allowed us to ensure that all three groups were comparable in terms of the

age, education level, BMI, eating frequency, ESL status, and gender ratios of the

participants. Had we failed to do so, we may have missed finding important differences

between the Augmented and Balanced conditions on the Ruff 2 & 7 Speed task and

between the Depleted and Balanced conditions on the Rey-O delay recall task. Thus, had

other studies employed all three levels of manipulation, perhaps more findings would be

present within the literature.

Another strength to the present study is that our test battery was a fairly

comprehensive assessment of cognitive functioning, consisting of reliable and well-

validated measures that are commonly used clinically. Our inclusion of a visuospatial

measure of LTM, a task often omitted from the test battery of other researchers, enabled

the detection of group differences between males in the Depleted and Balanced

conditions.

A final strength to the present study, compared to many studies in the literature,

pertains to the sample collected. We obtained roughly the same female to male ratio in

each of the three meal conditions (approximately 2:1, respectively), whereas many past

studies have included only male (e.g., Hughes et al., 2003; Park et al., 1994) or only female participants (e.g., Nabb & Benton, 2006). While it might be argued that the sample employed in the present study was too small, there are several findings within the Tryptophan 135

literature that support the sample size and gender split utilized. A mega-analysis by

Sambeth and colleagues (2007) was conducted on nine studies employing acute tryptophan depletion in order to investigate the effects of tryptophan depletion on declarative LTM and the mediating variables of age, gender and serotonergic dysregulation. Their results indicate that tryptophan depletion results in lower scores on measures of delayed (and, to some degree, immediate) recall, but that the effect is larger for women. Further, they noted that gender was the only variable found to be a factor of serotonergic vulnerability. The difference in tryptophan levels between the depletion and control conditions was 9.90 for females (effect size = .60), but only 4.13 for males (effect size = .29). They calculated that the sample size required for a power of .8 (deemed a large effect size, according to Cohen, 1992) is 19 for females, but 74 for males. This female sample size is not altogether dissimilar from that collected in the present study

(Augmented = 17 females; Balanced = 17 females; Depleted = 16 females; total female n

= 50). Cohen (1992) states that for a three group ANOVA with a large effect size (.8) using alpha at .05, a total of 21 participants per group are required; this number is less than that collected in the present study, provided we collapse across gender (Augmented, n = 25; Balanced, n = 25; Depleted, n = 23) . If gender is considered (i.e., a six group

ANOVA), a total of 14 participants per meal and gender group would be needed (Cohen,

1992). The present study has more than 14 participants in each meal condition (collapsed across gender), but admittedly fewer than 14 males per meal condition when gender is taken into account. There are, however, more than 14 females in each condition.

Further, as discussed by Sambeth’s group (2007), the effect of tryptophan manipulation is carried by females, not males, which suggests that our current female sample size is Tryptophan 136

likely adequate. This point is particularly relevant as the mega-analysis by Sambeth and

colleagues (2007) only included studies that employed verbal measures of LTM. As the

present study found effects for males on a measure of visuospatial LTM, our smaller

male sample size is likely not an issue. Lastly, examination of the sample sizes of other between-subject studies within the literature that employed a dietary manipulation of

tryptophan reveals that most contain cell sizes that are either comparable to, or much

smaller than, those in the present study (for both males and females). For example,

Vered (2001) reported cell sizes of between 4 and 6, Rogers and colleagues (1999) report

cell sizes of between 7 and 8, and Markus’s group (1998) reports cell sizes ranging from

6 to 18. Other, larger studies, such as Spring and colleagues (1982) do not explicitly state

their cell sizes, only informing the reader that their 184 participants were split into 4

groups, that 129 were male, 55 were female, and that 81 were aged 18-36, whereas 103

were aged 40-65. Similarly, Lieberman’s group (2002) collected a total sample size of

143 male participants randomly assigned to three groups, but does not indicate the exact

number of participants per condition, leaving the reader to speculate that approximately

47 participants were in each condition. Lastly, Nabb and Benton (2006) report that they

collected data on 189 female participants who were then split into 8 groups with between

23 and 25 participants each. Overall, these studies indicate that the sample size of the

present study is at least comparable to, if not greater than, the standard reported within

the literature which, when taken together with the findings of Sambeth’s group and the

established power analyses of Cohen (1992), indicate the adequacy of the sample in the

present study. Thus, the sample size in this study may be considered a relative strength in

comparison to many studies (particularly those employing a between-subjects design), Tryptophan 137

but also a weakness in terms of Cohen’s established levels of adequate power (but only

with regard to the males).

Regardless, what is of interest is that unlike Sambeth and colleagues’ (2007) findings that females carry the effect for tryptophan depletion lowering verbal LTM, the present study found that males carried the effect for tryptophan depletion improving

visuospatial LTM. This finding is perhaps due to gender effects showing that males are

better at visuospatial tasks than are females (Burnett et al., 1982; Kaploun & Abeare,

2007; Lewis & Harris, 1990; Linn & Petersen, 1985; Peters et al., 1995) (although these

findings largely disappear when degree of hemispheric lateralization is taken into

account; e.g., Burnett, Lane & Dratt, 1982; Kaploun & Abeare, 2007; McGlone &

Kertesz, 1973; McGlone, 1980). It is also possible that the smaller sample of males

(compared to females in this study) made individual differences stand out more, allowing

them to influence results more than would be the case with a larger sample of males.

Lastly, it could be that these findings are the result of some peculiarity of the sample that

cannot be accounted for and that may not likely be replicated by other researchers.

Whatever the reason, future research should be sure to include equal numbers of men and

women in their sample as this appears to be an important factor in influencing results.

Overall, these factors indicate that our investigation was a strong test of the

hypothesis that dietary manipulation of tryptophan levels affects cognitive functioning

and affective processes.

Limitations of the Current Study

There are, however, some limitations to this study. First, in deference to the

within-subject design commonly found within the literature, the present study employed a Tryptophan 138 mixed design. Although such a design does introduce inter-individual variability that would otherwise be absent in a within-subject study, it does reduce the chances of test expectancy and repeated testing influencing results, as well as enabling the recruitment of larger sample sizes with lower attrition rates. This latter point is key as differences in the findings of previous studies and the present one could be due to sample size of the males.

Thus, it could be that individual differences get disproportionately represented in small within-subject studies due to the lack of variability within the sample itself. This could be the reason for the results found for the PANAS PA and the trend in Excitement levels for males in the present study. This problem is avoided by mixed designs employing between-subject variables with larger samples.

Another limitation was that we were unable to draw blood assays in order to assess for alterations in free and total plasma levels of tryptophan, resulting in the inability to definitively discern whether or not the dietary manipulation successfully altered circulating tryptophan levels. As several other studies reported in the literature, however, have similarly failed to draw blood samples from participants (e.g., Kanarek &

Swinney, 1990; Lieberman et al., 2002; Smith et al., 1988; Spring et al., 1983), it was not felt that this was a strong limitation. There are, in addition, several theoretical and practical reasons for rightfully excluding the use of blood assays. For instance, although sampling blood would enable us to determine whether the dietary manipulation successfully altered circulating tryptophan levels, it does not allow us to definitively determine whether the levels of tryptophan in the brain have been similarly altered.

Based on this data, we can infer that a change has occurred, but we have no way of directly measuring brain tryptophan levels or the levels of its metabolites, including Tryptophan 139

serotonin. One means of measuring tryptophan metabolism is to measure levels of 5-

HIAA (the end product of metabolized serotonin) in cerebral spinal fluid (CSF). It has been assumed that CSF levels of 5-HIAA indicate how much serotonin has been produced and released in that higher levels of CSF 5-HIAA would correlate with greater serotonergic activity. For example, in a study by Carpenter and colleagues (1998), a sample of 5 healthy participants (3 male, 2 female) underwent a tryptophan depletion protocol (amino acid drink) and then had their lumbar CSF sampled every 15 minutes over a 13.5 hour time span. The researchers utilized 5-HIAA as a measure of central serotonin levels, and collected blood samples to measure plasma levels. Despite the counterintuitive findings that a 92% drop in CSF 5-HIAA levels and an 85% decrease in blood tryptophan levels occurred, no behavioural or mood changes were found following tryptophan depletion. From these results, there can be no doubt that tryptophan levels changed (at least in free-circulating blood levels), but whether these changes lead to decreases in brain tryptophan or its metabolites, such as serotonin, is unclear. Further, it is unclear as to whether such changes in blood serum tryptophan levels are even related to CSF tryptophan levels. It has been found by several researchers (e.g., Perez-Cruet,

Chase & Murphy, 1974; S. N. Young et al., 1976), however, that it is not CSF tryptophan

levels, but rather free tryptophan blood serum levels, that correlate with CSF 5-HIAA.

Together, these findings suggest that CSF 5-HIAA levels can only be used to indirectly

estimate the degree of change in central nervous system tryptophan and serotonin levels

(Carpenter et al., 1998; Degrell & Nagy, 1990; Nishizawa et al., 1997). What is more,

Anderson and colleagues (1990) assert that since serotonin concentrations in CSF are

extremely low and the current methods available for detecting subtle changes in central Tryptophan 140

(i.e., brain) CSF are imprecise, it is not clinically useful to assess central serotonin

activity via CSF analysis. Furthermore, Garelis, Young, Lal and Sourket (1974) assert

that lumbar CSF may include 5-HIAA from brain or spinal catabolism of serotonin,

highlighting the fact that lumbar CSF may not be directly related to brain (i.e.,

ventricular) CSF. Urinanalysis of 5-HIAA levels has also been utilized to detect

serotonergic production and release throughout the body. As discussed earlier, an adult

male human body contains approximately 10 mg of serotonin; roughly 1-2% of that 10

mg is found within the brain (Sirek & Sirek, 1970). Thus, 5-HIAA in urine could be

from tryptophan metabolism anywhere in the body, not just in the brain. Furthermore, 5-

HIAA is usually only found in very small quantities in urine as larger amounts are

indicative of carcinoid tumors (Feldman, 1986). Thus, it is clear that urinalysis of 5-

HIAA is an inadequate means of measuring brain tryptophan or serotonin as there is no way to determine if the 5-HIAA is a result of central or peripheral tryptophan metabolism.

Overall, it should be clear that although blood assays would enable one to ensure whether or not a tryptophan manipulation actually altered serum levels of tryptophan

within the circulating blood, it is an inadequate measure of brain tryptophan levels.

Furthermore, there is no direct way to measure tryptophan or serotonin levels in the brain

as neither lumbar nor ventricular tryptophan or serotonin levels can directly assess the

availability of these substances in the brain. Taken together, these findings suggest that

employing blood assays as a measure of tryptophan levels in the brain is not necessarily a

requirement in this field of research as it is at best an indirect method of inference.

Tryptophan 141

Is Dietary Manipulation An Effective Means of Measuring Tryptophan Manipulation?

Although the present study did not detect as many effects of tryptophan manipulation as would have been hoped, there are several reasons why it is felt that the dietary method of tryptophan manipulation is worth pursuing. As discussed earlier, it is a relatively inexpensive and a much more feasible means of manipulating tryptophan levels

(compared to the amino acid protocol), enabling more researchers who do not have large research grants to implement this method. Purchasing fresh foods and bulk items is relatively economical, even for those with small research budgets. This fact alone should make it a much more appealing alternative to researchers looking to work within this field of study. Using different samples and designs, several researchers have shown that dietary methods of tryptophan manipulation do produce cognitive and affective changes in participants (e.g., Fischer et al., 2002; Lieberman et al., 2002; Markus et al., 1998;

Smith et al., 1988). As more researchers employ this method, our knowledge about the effects of dietary manipulations will continue to increase which will help bring about some consensus within the field as to the appropriate amounts of each food, and other methodological and research issues concerning the effects of tryptophan upon cognition and affect.

Furthermore, it must be kept in mind that this line of research is still in its infancy.

While it is true that the backbone of this field of study arguably started in 1948 with the isolation of serotonin, it has hopefully been made clear that no consensus has been reached as to the appropriate design and method of this type of research. At present, the literature is a veritable cornucopia of differing sample sizes and demographics, methodologies (dietary or amino acid mixture), designs (within-, between-, and mixed- Tryptophan 142

designs), and other possibly confounding variables that make it extraordinarily difficult to

arrive at consistent, replicable, and generalizeable results. As more researchers pursue

this line of study greater consensus will begin to emerge within the literature, which should also help bring us closer to a unified theory.

It must also be kept in mind that this line of research is incredibly complex. All research must take into account such variables as individual differences and other confounding factors, but within this field of study there are a myriad of other factors that could bear weight upon the outcome, such as inherent differences in macronutrient metabolism and catabolism, as well as the production and activity of resulting

neurotransmitters. The interplay between different amino acids and macronutrients, as

well as between different neurotransmitters, may also influence whether or not effects of

the tryptophan manipulation are detected. In other words, the same manipulation may be

much stronger for one participant than for another, even though all other variables are

similar. For this reason, this field of study may be better suited to the examination of

manipulation responders versus non-responders. By investigating these two groups

separately, we may begin to get a better picture of what makes someone a responder

versus as non-responder, as well as the ways in which they differ cognitively and

affectively following tryptophan manipulation.

The importance of this line of research cannot be overstated. It is not just students

or patients that would benefit from a greater understanding of the effects of tryptophan on

neuropsychological performance. If consumption of everyday foods was found to result

in significant effects on cognition or affect, then it is possible that in our daily lives we

are inadvertently affecting our baseline level of functioning. What is more, we could Tryptophan 143 unknowingly be exacerbating existing conditions or conditions to which we are predisposed (e.g., depression). For instance, patients taking monoamine oxidase inhibitors (MAOIs) for the treatment of depression must limit foods high in tyramine, such as cheese, alcohol, and chocolate to prevent spikes in blood pressure that could lead to stroke (McCabe, 1986). While it is not being argued that tryptophan, found in the levels present in everyday food, exert the same effects as major antidepressant medications, it could be that even trace amounts of tryptophan could interact with medications taken for various conditions. It is possible that even small amounts of tryptophan or other macronutrients could be enough to produce, without our even being aware of it, variations in our day-to-day behaviour (including mood, cognition, and physiological or metabolic states). Maier and Watkins (2000) have proposed a similar idea regarding our immune systems, suggesting that since we are continuously coming into contact with unknown pathogens, variations in our spontaneous “normal” behaviour are caused by immune system responses. Further, they state that in response to immune system activation, serotonin is released in the hippocampus, highlighting the complexities of human neuropsychological function and the many factors that can influence them.

Overall, it should be clear that the complexities of this field of research make it difficult to boil down results to one simple set of findings. The ease and accessibility of employing a dietary manipulation of tryptophan in order to investigate the effects of tryptophan manipulation on cognitive and affective outcomes should make this field of study more appealing to researchers, and through increased research the complexities of this area of research will begin to unravel.

Tryptophan 144

Summary and Future Directions

In conclusion, although no significant results were found for females, significant effects were found for males on the Rey-O delay recall, and the Ruff 2 & 7 Total Speed

measure, as well as minor differences in PA and excitement levels over time. These

findings are relatively unique within the literature as few studies have found significant

results for PA (as opposed to NA), or for visuospatial LTM, especially for males.

Although some caution must be exercised in comparing the results of the present study to

those of within-subject studies, it is apparent that the current study found effects of tryptophan manipulation that, to the best our knowledge, have not yet been reported within the literature. Unlike Lieberman and colleagues (2002), the present study did not find that carbohydrates resulted in increased vigilance in males, nor did it result in greater sleepiness in women, or greater calmness in men (Spring et al., 1983). Furthermore, no between-subject studies employing a dietary method of tryptophan manipulation found any effect of tryptophan on visuospatial LTM or on tests of selected visual attention.

Hoyland and colleagues (2008) bolster the belief of the author that the lack of consensus

within the literature pertaining to the effects of tryptophan manipulation could at least in

part be due to the variability of research designs and methods, with too few studies

employing the same means of manipulating tryptophan or of measuring its effect. They

also suggest that different foods likely produce cognitive effects along differing

timelines, and thus it might be best if performance (on cognitive measures) was assessed

on multiple occasions following the manipulation in order to assess differences in

performance across time. Furthermore, there is a lack of consensus within the literature

as to whether manipulating tryptophan levels in healthy participants, such as in the Tryptophan 145

present study and many others (e.g., Lieberman et al., 2002; Luciana et al., 2001; Riedel

et al., 1999), leads to findings as robust as those seen in psychiatric populations (e.g.,

Benkelfat et al., 1994; LeMarquand et al., 1998). Thus, a combination of participant characteristics, sample size, method of manipulation and test sensitivity could all be responsible for the lack of consistent findings within this field of research.

Future directions for this field of study should include the analysis of tryptophan manipulation responsiveness (as suggested earlier), coding participants as either responders or non-responders. This idea had occurred to the author of the present study after completing data collection. However, as this was not an a priori analysis, it was discovered that the data from the present study do not lend themselves to coding participants as responders or not. For this type of analysis to be done, a greater range of scores must be available on the pre- and post-test measures used to assess the effectiveness of the manipulation. The PANAS and Digit Span Backwards scores did not provide the ranges required to discern not only whether someone responded to the manipulation, but also whether or not they responded in the predicted direction based on their meal condition. Responder analyses were attempted, but they were deemed meaningless as the categories for ‘responder’ or ‘non-responder’ were far too narrow, making it impossible to accurately determine whether a participant did in fact respond to the manipulation (in the manner predicted or not). Future studies should consider this analysis from the start of their design conception and should detail exactly how they will define and code for responsiveness in order to ensure an adequate range of scores is attainable. Tryptophan 146

Other, more technologically complex designs should also be considered for

future research. For instance, PET studies employing the injection of radio-labelled

tryptophan would also provide a wealth of information concerning whether exogenous

doses of tryptophan actually increase brain tryptophan (and therefore serotonin

production and release), and whether such changes are detectable via behavioural or

affective output. In a study by Perreau-Linck and colleagues (2007) using PET,

professional actors were instructed to self-induce a particular mood state (happy, sad or

neutral, counterbalanced across 3 testing days) and were then injected with radio-labelled

tryptophan (11C-labelled α-methy-L-tryptophan, a synthetic version of L-tryptophan that

crosses the blood-brain barrier and is used to estimate serotonin synthesis within the

brain). Although no changes were detected in free or total venous tryptophan levels, the

researchers found that serotonergic activity in the right anterior cingulate cortex was positively correlated with self-induced happiness, whereas a negative correlation was found between self-induced sadness and the subcallosal region of the right anterior cingulate cortex. These results indicate that even though measurable levels of free circulating tryptophan did not appear to change, changes to serotonin activity within the brain were detected. In a similar vein, Praschak-Reider and colleagues (2004) conducted a tryptophan depletion study using PET with 8 currently-remitted depressed patients.

Although they measured a drop of 86% in total tryptophan plasma following tryptophan depletion, they failed to detect any changes in brain serotonin levels or activity. The tryptophan depletion did, however, induce a transient relapse of depressive symptoms in

6 of their 8 participants, indicating that small changes in brain serotonin levels are sufficient to induce short-term relapse in depressed patients normally being treated with Tryptophan 147

SSRIs. Taken together, these studies seem to suggest that even small changes in brain tryptophan or serotonin levels can lead to changes in activity in neuroanatomical structures known to be implicated in mood. Future studies should include a more comprehensive assessment of other neuropsychological functions, such as memory or attention. Hoyland and colleagues (2008) suggests that the following tests seem most consistently sensitive to macronutrient manipulation: the serial sevens task (a measure of working memory); free word recall with delay trials (verbal LTM); and cued word recall

(verbal LTM). Thus, the inclusion of measures similar to these should be employed in

PET studies.

As a follow-up to the present study, a mixed-design study should be employed with both between- and within-subject participants being recruited. Such a design will allow the direct comparison of these two methods to help determine which is the stronger design. This finding would guide researchers in deciding which design to utilize in future research. A larger sample size for both between- and within-subject samples, with equal gender ratios in each condition, should be obtained to further strengthen the findings of the present study and to prevent possible power issues from confounding results. The inclusion of additional sensitive measures, such as those suggested by Hoyland and colleagues (2008), should also be employed to provide the widest net for catching any between-group or between-condition effects of tryptophan manipulation on neuropsychological performance.

Overall, through future research that employs the above-discussed methods of measuring and assessing tryptophan and serotonin levels in the brain, a better Tryptophan 148 understanding of the effects of tryptophan manipulation on neuroanatomical, cognitive and affective functioning should begin to emerge.

Tryptophan 149

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Young, S. N., Ervin, F. R., Pihl, R. O., & Finn, P. (1989). Biochemical aspects of

tryptophan depletion in primates. Psychopharmacology, 98, 508-511.

Young, S. N., Lal., S., Feldmuller, F., Sourkes, T. L., Ford, R. M., Kiely, M., et al.

(1976). Parallel variation of ventricular CSF tryptophan and free serum

tryptophan in man. Journal of Neurology, Neurosurgery, and Psychiatry, 39, 61-

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Young, S. N., Smith, S. E., Pihl, R. O., & Ervin, F. R. (1985). Tryptophan depletion

causes a rapid lowering of mood in normal males. Psychopharmacology, 87, 173-

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Young, V. R. (1994). Adult amino acid requirements: The case for a major revision in

current recommendations. The Journal of Nutrition, 124 (8 Suppl), 1517S-1523S.

Zohar, J., & Westenberg, H. G. (2000). Anxiety disorders: A review of tricyclic

antidepressants and selective serotonin reuptake inhibitors. Acta psychiatrica

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Tryptophan 180

Appendix A

Glossary of Terms

CNS Central Nervous System: the part of the nervous system comprised

of the brain and spinal cord that coordinates activities of the body.

LNAAs Large Neutral Amino Acids: a term used to describe amino acids

that compete with each other for uptake into the brain and

subsequent neurotransmitter synthesis.

5-HT The chemical name for the neurotransmitter 5-hydroxytryptamine

(aka: serotonin), the final end product of tryptophan metabolism.

5-HTP The chemical name for 5-hydroxytryptophan, the amino acid

metabolite of tryptophan and the precursor to serotonin (5-HT).

5-HIAA The chemical name of 5-hydroxyindoleacetic acid, the primary

metabolite of serotonin (5-HT) that is excreted in the urine.

Depletion The term used to denote acute tryptophan depletion produced

either via the amino acid protocol drink, excluding the amino acid

tryptophan, or via dietary manipulations (i.e., protein-loading).

Augmentation The term used to denote acute tryptophan augmentation produced

either via the amino acid protocol drink, with the inclusion of

increased amounts of the amino acid tryptopahn, or via dietary

manipulations (i.e., carbohydrate-loading).

Balanced The term used to denote the balanced condition between acute

tryptophan depletion and acute tryptophan augmentation, produced Tryptophan 181

either via the amino acid protocol drink, wherein the proportion of

LNAAs produces an equal effect as the amount of tryptophan on

plasma levels, or via dietary manipulations (i.e., the

carbohydrate:protein ratio produces an even balance between

LNAAs and tryptophan).

BMI Body Mass Index: a measure of body fat based on weight and

height. Tryptophan 182

Appendix B

Study Advertisement (Participant Pool)

Participant Pool Recruitment Statement – Effects of Food on Cognition

Hello,

My name is Kristen Kaploun and I am a PhD Candidate in the Clinical Neuropsychology program here at that University of Windsor. I am contacting you in the hopes that you are interested in taking part in my research study examining the effect of food on cognition. This is a two-part study, requiring participants to first take part in a screening session; it is this session for which I am now recruiting participants. The purpose of this screen is to determine your eligibility for inclusion in the study entitled, “The Effects of Food on Cognition”. This screening is completely non-invasive. If you volunteer to participate, you will be asked to come into the laboratory for approximately 30 minutes in order to complete a screening interview. During the interview, you will be asked to provide information about your medical history and general health, as well as other demographic criteria (e.g., age, gender, program of study). The screen is worth 0.5 credits. If you are deemed eligible to continue, and you wish to do so, a separate appointment will be set up for you to come in and take part in the testing session. The testing session takes approximately 5.5 hours, during which time you receive breakfast, lunch and two snacks. The testing session is worth 5.5 credits and the chance to win one of two $50 gift cards (more information will be provided about the study during the screening session). If you are interested in taking part, please email me at: [email protected] and we can set up an appointment. The screening will take place in the basement of Chrysler Hall South, Room 73.

I thank you in advance and I look forward to hearing from you. Tryptophan 183

Appendix C

SCREENER

Effects of Food on Cognition

*Are you allergic to peanuts? □ No □ Yes If Yes, please leave now ______

Date: ______

Age: _____

Sex: _____ ESL?: _____

Weight: ______

Height: ______

BMI: ______(BMI category: ______)

• Underweight = <18.5 (less than 17.5 = anorexia) • Normal weight = 18.5 - 24.9 • Overweight = 25 - 29.9 • Obesity = BMI of 30 or greater

Do you have any food allergies? □ No □ Yes If Yes: ______

Chronic illnesses? (incl. Crohn’s disease, celiac disease, IBS, lactose intolerance)

• ______• ______• ______• ______• Do you have diabetes? □ No □ Yes If ‘Yes’, Type I or II ?

Current illnesses?

• ______• ______• ______Tryptophan 184

• ______

Current medications? (incl. birth control, vitamins, herbal supplements, allergy or asthma meds)

• ______• ______• ______• ______

Exclusionary: SSRIs, MAOIs, narcotics, anti-psychotics, anti-depressants, anxiolytics (anti-anxiety)

Do you use any recreational drugs? □ No □ Yes If Yes: ______

Hallucinogens: PCP, angel dust, ketamine, Special K, LSD, acid, MDMA/methamphetamine, ecstasy, mescaline, peyote, psilocybin (mushrooms)

Frequency: ______Amount: ______

Pain Killers: Codeine, opium, heroin, morphine, smack, Vicodin, methadone, Dilaudid, Oxycodone/Oxycontin, Percodan

Frequency: ______Amount: ______

Tranquilizers: Benzodiazepines, Valium, Ativan, Diazepam, pentobarbital, amobarbital, Seconal, roofies, Nembutal, barbituates, inhalants, alcohol

Frequency: ______Amount: ______

Stimulants: Cocaine, coke, crack, amphetamines, methamphetamines, speed, crystal meth, ice, crank, Ritalin, tobacco, caffeine

Frequency: ______Amount: ______

Marijuana: Marijuana, pot, weed, hashish, hashish oil

Frequency: ______Amount: ______

Steroids: Any kind: ______

Frequency: ______Amount: ______Tryptophan 185

Any prescription? □ No □ Yes Yes: ______

Do you smoke? □ No □ Yes

If Yes: How many per day?______How long have you smoked? ______

Is your diet irregular? □ No

□ Yes: ______

Does your weight tend to fluctuate? □ No □ Yes Range: ______

Have you ever / do you ever binge eat? □ No □ Yes When last?______

Have you ever been diagnosed with: Anorexia Nervosa □ No □ Yes Bulimia □ No □ Yes

Do you usually eat breakfast? □ No □ Yes

Do you usually eat lunch? □ No □ Yes

Athleticism: □ Very □ Quite □ Minimal □ Not at all (daily) (3-5 time/wk) (e.g., walk to school) (e.g., drive to school)

Metabolic Rate: How often do you eat during a normal day (every X hours): ______

Do you eat more than most people at each meal? □ No □ Yes

What types of foods do you crave the most? ______

Current Depression? □ No

□ Yes:______

Current Anxiety? □ No

□ Yes:______Tryptophan 186

Family history of mental illness? (include who has what disorder)

• ______• ______• ______• ______

History of stroke, seizures or other neurological impairments/injuries? (incl. age of injury and most recent event) • ______• ______• ______• ______

How many hours of sleep do you get in a typical night? ______Do you feel rested upon waking? ______

How much caffeine do you typically consume in a day? □ Pop: ______□ Coffee: ______□ Decaf Coffee: ______

□ Decaf Pop: ______□ Tea: ______□ Decaf Tea: ______

□ Chocolate: ______□ Hot Chocolate: ______

□ Energy Drinks: ______□ Other: ______Do you ever take caffeine pills? ______

Other: Are you pregnant? □ No □ Yes Stage of menstrual cycle (females only): Last day: ______First day: ______

General

How did you find out about this study? ______

¾ Recruitment method (circle one): Participant Pool Poster Tryptophan 187

What motivated you to take part in this study? ______

Are you a student? □ No □ Yes

If ‘Yes’, what is your Major? ______¾ What year are you currently in? ______

If ‘No’, what kind of work do you do? ______Tryptophan 188

Appendix D

Study Advertisement (Community Sample)

INTERESTED IN THE EFFECTS OF FOOD ON COGNITION?

Women and men 17 years or older are invited to participate in a study exploring the effects of food on cognitive performance.

Participation is voluntary and confidential. Participants will receive breakfast, lunch and two snacks, as well as the chance to win 1 of 2 gift cards valued at $50 for a total of 6 hours of their time (30 minutes for the pre-screening, and 5.5 hours for the testing session).

This study is being conducted by Kristen Kaploun, M.A., a clinical neuropsychology doctoral student at the University of Windsor, and her research advisor, Dr. Chris Abeare, Ph.D. The research study has received ethics clearance from the University of Windsor Research Ethics Board.

For further information about this study, please contact Kristen at [email protected].

[email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at: [email protected] Contact Kristen at:

Tryptophan 189

Appendix E – Screener Consent Form

CONSENT TO PARTICIPATE IN SCREEN

To determine eligibility for participation in the study entitled, “The Effects of Food on Cognition”

Title of Study: The Effects of Food on Cognition

You are asked to participate in a research screen for a study conducted by Kristen Kaploun, MA (student researcher) and Dr. Chris Abeare, PhD (faculty supervisor), from the Psychology Department at the University of Windsor. This screen comprises a part of Kristen Kaploun’s PhD Dissertation.

If you have any questions or concerns about the research, please feel free to contact Kristen Kaploun at [email protected], or Dr. Chris Abeare at 519-253-3000, ext. 2231.

PURPOSE OF THE STUDY

The purpose of this screen is to determine your eligibility for participation in the study, “The Effects of Food on Cognition”.

PROCEDURES

If you volunteer to participate in this screen, we would ask you to do the following things:

Screening Procedures:

Upon signing up for the study, you will be asked to come into the laboratory. Upon providing informed consent, you will be asked to complete an initial screening interview. You will be asked you will be asked to provide information about your medical history and general health, as well as other demographic criteria (e.g., age, gender, program of study). If you are deemed eligible to participate in the study and you wish to do so, a separate appointment will be made for you to return to the lab to take part in the study. The screening session should last approximately 30 minutes and will take place one-on-one with the examiner in the basement of Chrysler Hall South, Room 73. It is worth 0.5 credits.

Exclusionary Criteria:

Participants will be excluded if they meet criteria for any of the following:

- Obesity, Anorexia, or Bulimia (other eating disorders) - Diabetes - Food allergies - Lactose intolerance - Irritable Bowel Syndrome (IBS) Tryptophan 190

- Crohn’s disease - Celiac disease - Other chronic illnesses (incl. Endocrine and metabolic disorders) - Current depression - Current anxiety - Illicit drug use (e.g., marijuana, narcotics) - Stimulants (incl. more than the equivalent of 5 cups of coffee/day, or 1 package of cigarettes/day) - Current medication use (incl. SSRIs, MAOIs, psychotropic medications, cold medications such as Nyquil) - History of neurological disorders/impairments

POTENTIAL RISKS AND DISCOMFORTS

All information provided is completely confidential. However, it is possible that by participating in this screen, you may experience discomfort discussing medical and health matters. If so, you may elect to skip certain questions and still remain in the screen.

If by taking part in this screener you experience certain negative feelings, such as anxiety, sadness or worry, and you would like to talk to someone about these feelings, here is a list of local resources that we encourage you to contact:

The Student Counseling Centre CAW Student Centre Room 293 2nd Floor (519) 253-3000 Ext. 46160 Email: [email protected]

Windsor Regional Hospital Mood and Anxiety Clinic (519) 257-5125

Windsor Mood Disorders Self-Help Group (519) 979-5089

Community Crisis Centre (519) 973-4435

POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY

By participating in this screen, you will learn about the different variables that may influence the effects of meal composition on cognitive performance. If you are deemed eligible to take part in the study upon completion of the screen, you will learn more specific information regarding the impact of food choices on cognition. The scientific community, society and those involved in helping patients who experience transient or occasional cognitive, affective, or physiological problems could benefit from a greater understanding of role played by various food components on mood and cognition.

PAYMENT FOR PARTICIPATION

As a participant, you will earn 0.5 credits for participating in this screen. If you are deemed eligible for taking part in the testing session and you wish to do so, you will be able to earn up to an additional (and maximum of) 5.5 credits for completing the study (please note that credits cannot be “banked” from one semester to another). If you are deemed eligible to take part in the testing session, more information will be provided about the procedures, at which point you may decide if you want to take part. Even if you chose to not take part in the testing session (i.e., upon hearing the details it is not of interest to you), you will still earn the 0.5 credits for taking part in the screening session. Tryptophan 191

CONFIDENTIALITY

Any information that is obtained in connection with this study and that can be identified with you will remain confidential and will be disclosed only with your written permission. Your identity will be known to the researcher for the purposes of scheduling and compensation only and any information collected will be kept in file cabinets and locked up in the laboratory. Upon entering the lab for the study screen, you will be assigned an ID number. This number is kept on a master key alongside your name and contact information. All data that is subsequently collected will be identifiable by ID number only. All data will be stored in cabinets and locked up in the laboratory; the master key, which will be stored separately from all data, will also remain locked in the laboratory. Data will be retained, locked away in this fashion, for at least two (2) years until the study is completed and accepted for publication.

PARTICIPATION AND WITHDRAWAL

You can choose whether to be in this screen or not. If you volunteer to be in this screen, you may withdraw at any time. However, please note that if you decide to withdraw from the screen, you will only be compensated for the time in which you participated (i.e., a maximum of 0.5 credits). The investigator may withdraw you from this research if circumstances arise which warrant doing so (for example, if you fail to follow test instructions, or if it is deemed unsafe for you to continue to participate). As a participant in this study, you will have the option of removing your screening data from the study.

FEEDBACK OF THE RESULTS OF THIS STUDY TO THE SUBJECTS

Participants will have the option of learning the results of the study (not the screen) simply by contacting the researcher. Those who are ineligible for participating in the study will be notified and provided with the reason for their exclusion. Participants who complete the study may also log onto the REB website and read the results of this study by selecting it from the available list.

Web address: http://www.uwindsor.ca/reb Date when results are available: April 30, 2011

SUBSEQUENT USE OF DATA

This data will be used in subsequent studies.

RIGHTS OF RESEARCH SUBJECTS

You may withdraw your consent at any time and discontinue participation without penalty. If you have questions regarding your rights as a research subject, contact: Research Ethics Coordinator, University of Windsor, Windsor, Ontario, N9B 3P4; Telephone: 519-253-3000, ext. 3948; e-mail: [email protected]

SIGNATURE OF RESEARCH SUBJECT/LEGAL REPRESENTATIVE

I understand the information provided for the screen for the study “The Effects of Food on Cognition” as described herein. My questions have been answered to my satisfaction, and I agree to participate in this screen. I have been given a copy of this form.

Tryptophan 192

______Name of Subject

______Signature of Subject Date

SIGNATURE OF INVESTIGATOR

These are the terms under which I will conduct research.

______Signature of Investigator Date

Tryptophan 193

Appendix F – Testing Session Consent Form

CONSENT TO PARTICIPATE IN RESEARCH – TESTING SESSION

Title of Study: The Effects of Food on Cognition

You are asked to participate in a research study conducted by Kristen Kaploun, MA (student researcher) and Dr. Chris Abeare, PhD (faculty supervisor), from the Psychology Department at the University of Windsor. This study comprises Kristen Kaploun’s PhD Dissertation.

If you have any questions or concerns about the research, please feel free to contact Kristen Kaploun at [email protected], or Dr. Chris Abeare at 519-253-3000, ext. 2231.

PURPOSE OF THE STUDY

The purpose of this study is to determine the effects of different foods on cognitive performance.

PROCEDURES

If you volunteer to participate in this study, we would ask you to do the following things:

Testing Procedures:

On the day of testing, informed consent will be obtained along with a short intake survey. You will have been randomly assigned to one of three conditions, each of which receive a different set of meals. Upon completing the intake survey you will be provided with breakfast; lunch, and two snacks will also be provided before the end of the testing session. Please note that you will not have the option of refusing to eat some or all of the food provided during this study. If you do not wish to eat some or all of the food that is provided, you are free to withdraw at any time. If you chose to exercise this right, please note that you will only be compensated for the time in which you participated (i.e., you will not receive the full 5.5 credits; please see ‘Participation and Withdrawal’ section below for further details). One and a half hours following the provision of lunch, you will complete the test battery, comprised of several paper-and-pencil measures aimed at assessing various cognitive functions (e.g., attention). Indices of mood and affect will also be administered upon arrival at the laboratory on the day of testing, after each meal, and upon completion of the test battery.

The total length of time for participation will be approximately 5.5 hrs done in one sitting (the actual testing session will last approximately 1.5 hours). During the waiting period, you must remain in the waiting room (save for washroom breaks). You will be allowed to study, read, watch a movie on the computer or play a board game; you will not, however, be permitted to eat or sleep. Water will be provided upon request. This study will take place one-on-one with the examiner in the basement of Chrysler Hall South, Room 73 (the same room as the screening interview).

Tryptophan 194

Exclusionary Criteria:

Participants will be excluded if they meet criteria for any of the following:

- Obesity, Anorexia, or Bulimia (other eating disorders) - Diabetes - Food allergies - Lactose intolerance - Irritable Bowel Syndrome (IBS) - Crohn’s disease - Celiac disease - Other chronic illnesses (incl. Endocrine and metabolic disorders) - Current depression - Current anxiety - Illicit drug use (e.g., marijuana, narcotics) - Stimulants (incl. more than the equivalent of 5 cups of coffee/day, or 1 package of cigarettes/day) - Current medication use (incl. SSRIs, MAOIs, psychotropic medications, cold medications such as Nyquil) - History of neurological disorders/impairments

POTENTIAL RISKS AND DISCOMFORTS

It is possible that by participating in this study, you may experience a mild alteration of your mood (e.g., mild irritation or lowering of mood). Any such effects, if experienced at all, will be mild and transient, consistent with what might occur had you skipped breakfast or lunch. The snack provided upon completing the testing will help return your mood to baseline levels should any deviation occur.

If by taking part in this study you experience certain negative feelings, such as anxiety, sadness or worry, and you would like to talk to someone about these feelings, here is a list of local resources that we encourage you to contact:

The Student Counseling Centre CAW Student Centre Room 293 2nd Floor (519) 253-3000 Ext. 46160 Email: [email protected]

Windsor Regional Hospital Mood and Anxiety Clinic (519) 257-5125

Windsor Mood Disorders Self-Help Group (519) 979-5089

Community Crisis Centre (519) 973-4435

POTENTIAL BENEFITS TO SUBJECTS AND/OR TO SOCIETY

You will learn about the effects of meal composition on mood and cognitive performance. The scientific community, society and those involved in helping patients who experience transient or occasional cognitive, affective, or physiological problems could benefit from a greater understanding of role played by various food components on mood and cognition.

Tryptophan 195

PAYMENT FOR PARTICIPATION

Participants will earn up to a maximum 5.5 course credits for participating in, and completing, this study (please note that credits cannot be “banked” from one semester to another). The screening session (completed previously) is worth 0.5 credits. Thus, by fully completing this study, participants can earn up to a total of 6 credits (0.5 for the screening session, and 5.5 for the testing session). Completion of the study will also deem the participant eligible for inclusion (if s/he so wishes) in a draw to win 1 of 2 gift cards valued at $50 CAD to either Devonshire Mall or Future Shop. Please refer below (“Participation and Withdrawal”) for information regarding withdrawing from this study.

CONFIDENTIALITY

Any information that is obtained in connection with this study and that can be identified with you will remain confidential and will be disclosed only with your written permission. Your identity will be known to the researcher for the purposes of scheduling and compensation only and any information collected will be kept in file cabinets and locked up in the laboratory. Upon entering the lab for the study screen, you were assigned an ID number. This number is kept on a master key alongside your name and contact information. All data that is subsequently collected will be identifiable by ID number only. All data will be stored in cabinets and locked up in the laboratory; the master key, which will be stored separately from all data, will also remain locked in the laboratory. Data will be retained, locked away in this fashion, for at least two (2) years until the study is completed and accepted for publication.

PARTICIPATION AND WITHDRAWAL

You can choose whether to be in this study or not. If you volunteer to be in this study, you may withdraw at any time. However, please note that if you decide to withdraw from the study, you will only be compensated for the time in which you participated. In other words, if you completed 2 hours of the study, you will receive 2 credits; if you completed 4 hours, you will receive 4 credits. Also, choosing not to complete the testing session will deem you ineligible for inclusion in the draw to win 1 of 2 gift cards valued at $50 CAD to either Devonshire Mall or Future Shop. However, as a participant in this study, you may refuse to answer any questions you do not want to answer and still remain in the study. The investigator may withdraw you from this research if circumstances arise which warrant doing so (for example, if you fail to follow test instructions, or if it is deemed unsafe for you to continue to participate). Lastly, in the event that you choose to withdraw from the study, you will still receive the credits you earned for participating in the screen (i.e., you will not be docked previously earned points). As an example, if you withdrew from the study after 2 hours, you would have earned a total of 2.5 credits – 2 for the study, and 0.5 for the screener completed previously. As a participant in this study, you will have the option of removing your data from the study.

FEEDBACK OF THE RESULTS OF THIS STUDY TO THE SUBJECTS

Participants will have the option of learning the results of the study simply by contacting the researcher. They may also log onto the REB website and read the results of this study by selecting it from the available list.

Web address: http://www.uwindsor.ca/reb Date when results are available: April 30, 2011

Tryptophan 196

SUBSEQUENT USE OF DATA

This data will be used in subsequent studies.

RIGHTS OF RESEARCH SUBJECTS

You may withdraw your consent at any time and discontinue participation without penalty. If you have questions regarding your rights as a research subject, contact: Research Ethics Coordinator, University of Windsor, Windsor, Ontario, N9B 3P4; Telephone: 519-253-3000, ext. 3948; e-mail: [email protected]

SIGNATURE OF RESEARCH SUBJECT/LEGAL REPRESENTATIVE

I understand the information provided for the study “The Effects of Food on Cognition” as described herein. My questions have been answered to my satisfaction, and I agree to participate in this study. I have been given a copy of this form.

______Name of Subject

______Signature of Subject Date

SIGNATURE OF INVESTIGATOR

These are the terms under which I will conduct research.

______Signature of Investigator Date

Tryptophan 197

Appendix G

Composition of tryptophan augmented (ATA), tryptophan depleted (ATD), and balanced

(B) meals and snacks.

Augmentation Meal Breakfast Bread – 1 slice (26 g) Low-fat margarine – 1 tbsp (14 g) Grape jam – 1 oz (28 g) Tea – black decaf – 1 cup (8 fl oz) (237 g) Sugar (in tea) – 2 tsp (4 g) Grape juice – 1 cup (253 g) Snack Black coffee (decaf) – 1 cup (8 fl oz) (237 g) Sugar (in coffee) – 2 tsp (4 g) 3 Musketeer candy bar – 1 2.13 oz bar (60 g) Lunch Bread – 1 slice (26 g) Low-fat margarine – 1 tbsp (14 g) Grape jam – 1 oz (28 g) Grape juice – 1 cup (253 g)

Depletion Meal Breakfast Bread – 2 slices (26 g each) Low-fat margarine – 1 tbsp (14 g) Cheese – low-fat mozzarella – 1 oz (28 g) Tea – black decaf – 1 cup (8 fl oz) (237 g) Milk (in tea) – whole milk – 1 oz (28 g) Snack

Coffee – decaf – 1 cup (8 fl oz) (237 g) Milk (in coffee) – 1% milk – 1 oz (28 g) Peanuts – roasted with salt – 1 oz (28 g) Lunch Bread – 2 slices (26 g each) Low-fat margarine – 1 tbsp (14 g) Roast beef – lean – 1 oz (28 g) Tryptophan 198

Balanced Meal Breakfast Bread – 1 slices (26 g each) Butter – salted – 1 pat (5 g) Grape jam – 2 oz (28 g each) Tea – black decaf – 1 cup (8 fl oz) (237 g) Sugar (in tea) – 2 tsp (4 g each) Snack Black coffee (decaf) – 1 cup (8 fl oz) (237 g) Sugar (in coffee) – 2 tsp (4 g) Milk – 1% milk – 1 oz (28 g) 2 fun-size “3 Musketeers” candy bars - (28 g) Lunch Bread – 2 slices (26 g each) Peanut Butter (unsalted) – 1 oz (28 g) Grape jam – 1 oz (28 g) Grape juice – 1 cup (253 g)

Final Snack for all groups: Yogurt cup Pineapple fruit cup

All meals were modeled after those used by Markus and colleagues (1998). They were created and analyzed using the NutritionData website (NutritionData, 2009). RDA values based on a 2,000 calorie diet for males and females aged 4 and over as indicated by the Canada Food Inspection Agency (http://www.inspection.gc.ca/english/fssa/labeti/guide/ch6e.shtml#a6_3). Tryptophan 199

VITA AUCTORIS

NAME: Kristen A. Kaploun

PLACE OF BIRTH Toronto, Ontario

YEAR OF BIRTH 1982

EDUCATION Lawrence Park Collegiate Institute, Toronto 1996-2001 University of Guelph, Guelph, Ontario 2001-2005 B.A. Honours University of Windsor, Windsor, Ontario 2005-2007 M.A. University of Windsor, Windsor, Ontario 2007-2010 Ph. D.